Lidé na fakultě
doc. Ing. Ivan Nagy, CSc.

rozklikni NABÍDKU

Publikace

informace pocházejí z univerzitní databáze V3S

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2025, Journal of Computational Science, 85, ISSN 1877-7511
Anotace:
In this paper, we address the task of modeling and predicting count data, with an application to traffic counts on selected urban roads in Prague. We investigated the relationship between multiple counts, designating one of them as the target variable (e.g., data from a key road section) and the others as explanatory counts. Defining traffic count data as the number of vehicles passing through a selected road section per unit of time, we use a framework based on Poisson models to develop a progressive methodology, which we compared with existing models. Working with multimodal count data, we propose the following main steps for the methodology: (i) cluster analysis of explanatory counts using recursive Bayesian estimation of Poisson mixtures; (ii) target count model estimation via local Poisson regressions at identified locations, capturing local relationships between target and explanatory counts; and (iii) prediction of target counts through real-time location detection. The algorithm’s properties were first investigated using simulated data and then validated with real traffic counts. Experimental results indicate that the proposed algorithm outperforms classical Poisson and negative binomial regressions, decision tree and random forest classifiers, as well as a multi-layer perceptron, in predicting traffic count data across various quality metrics, even for weakly correlated data. Applied to traffic count data, the promising performance demonstrated by the proposed algorithm offers an optimistic vision for traffic prediction and urban planning, suggesting its potential as a valuable tool for enhancing transportation efficiency by optimizing the timing of city traffic lights to improve traffic flow.
DOI:
10.1016/j.jocs.2025.102534
Typ:
Článek v odborném recenzovaném periodiku

Autoři:
Tetiana Reznychenko; doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2024, 2024 Smart City Symposium Prague (SCSP), New York, IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC), p. 1-5), ISBN 979-8-3503-6095-0, ISSN 2691-3666
Anotace:
The paper deals with a comparative analysis of three widely used data analysis methods: logistic regression, random forest, and neural networks. These methods have been evaluated in terms of accuracy, and computational efficiency and applied to different types of data sets, including both simulated and real MaaS data. The study aims to compare the efficiency of each method in classification tasks. The study leads to specific recommendations on which method to use under various circumstances, contributing to the decision-making process in data analysis projects. We have shown that random forests generally provide better accuracy and are resistant to over-training. Neural networks can achieve comparable performance under certain conditions, although at a high computational cost. Logistic regression shows limitations in dealing with complex data structures.
DOI:
10.1109/SCSP61506.2024.10552715
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Mgr. Iveta Kameníková, Ph.D.; doc. Ing. Ivan Nagy, CSc.; doc. Ing. Jakub Hospodka, Ph.D.
Publikováno:
2024, Applied Sciences, 14 (8), ISSN 2076-3417
Anotace:
Contrails created by aircraft are a very hot topic today because they contribute to the warming of the atmosphere. Air traffic density is very high, and current forecasts predict a further significant increase. Increased air traffic volume is associated with an increased occurrence of contrails and induced cirrus clouds. The scientific level of contrails and their impact on the Earth’s climate is surprisingly low. The scientific studies published so far are mainly based on global models, in situ measurements, and satellite observations of contrails. The research is based on observations of contrails in flight paths in the vicinity of Děčín and Prague, and the collection of flight and meteorological data. It focused on the influence of the meteorological situation on the formation of persistent contrails. The collected data on contrails and meteorological variables were statistically processed using machine learning methods for classification models. Several models were developed to predict and simulate the properties of contrails as a function of given air traffic and meteorological conditions. The Random Forests model produced the best results. Dependencies between meteorological conditions, formation, and contrail lifetime were found. The aim of the study was to identify the possibility of using available meteorological data to predict persistent contrails.
DOI:
10.3390/app14083199
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Ing. Bc. Petr Kumpošt, Ph.D.; Ing. Petr Richter, Ph.D.
Publikováno:
2024
Anotace:
This data was provided by the mobile measuring laboratory MobiLab from the Czech Technical University in Prague (https://mobilab.fd.cvut.cz). It presents four data sets with traffic counts measured every minute over a 24-hour period at the following four selected areas in Prague: Stodůlky (September 2021), Barrandov (June 2022), Radlice (September 2022), and Velká Chuchle (October 2022). At each location, 3 to 6 points were chosen where traffic counts were collected in all possible directions along the corresponding road section or intersection. Directions are denoted by numbers 1-4 in the columns of each measured point. This data will be used in the research paper, where detailed information about the traffic counts will be available. References to the paper will be added later.
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
Ing. Rudolf Vávra, Ph.D.; Gašparík, J.; doc. Ing. Vít Janoš, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2024
Anotace:
Tato disertační práce se zabývá koncepcemi vícestupňové obsluhy území ve veřejné dopravě se zaměřením na pásmovou obsluhu v monocentrických sítích. Cílem této práce je navrhnout model optimalizace pásmového jízdního řádu na základě přepravních a provozně-ekonomických kritérií. Nejprve jsou v práci shrnuty běžné formy vícestupňové obsluhy území a jejich přepravní a provozně-ekonomické charakteristiky, stejně jako jejich vliv na čerpání kapacity dráhy. Poté jsou shrnuty nejdůležitější aspekty, které vstupují do rozhodování o poloze pásmových stanic, tedy hranic mezi jednotlivými aglomeračními pásmy. V následném rozboru současného stavu poznání jsou analyzovány práce zaměřující se na optimalizace jízdních řádů a provozu z přepravního a provozně-ekonomického hlediska. Dále byl prověřen současný stav v oblasti metod a přístupů k volbě pásmových stanic. Následně je představen samotný návrh optimalizačního modelu a způsobu jeho použití. Součástí představení modelu je jeho testování, navržený model byl úspěšně otestován na 4 reálných železničních tratích v ČR. V závěru bylo následně formulováno možné směřování dalšího návazného výzkumu souvisejícího s řešenou problematikou.
Typ:
Disertační práce (PhD)

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2024, Neural Network World, 34 (2), p. 89-110), ISSN 2336-4335
Anotace:
This paper deals with the analysis of the relationship between locations and types of crime observed in the Czech Republic. Cluster analysis of crime data based on the recursive Bayesian mixture estimation algorithm is used to identify crime hotspots and estimate local models of crime type. The experiments report that the 2D configuration of the algorithm allows the detection of crime hotspots online. The 3D configuration provides 29% more accurate crime type models than 2D clustering and alternative data mining algorithms. For the data set used, it was determined in which crime hotspots the most serious and most frequent types of crime can be expected to occur with the highest probability. The limitation of the study is the artificial support of the 3D clusters by the fully continuous data vector with the recoded values of the crime type. The potential use of the algorithm is expected in online web applications for sharing information on criminal offenses managed by the Police of the Czech Republic with the public and local government entities in the Czech Republic.
DOI:
10.14311/NNW.2024.34.006
Typ:
Článek v odborném recenzovaném periodiku cizojazyčně

Autoři:
Tetiana Reznychenko; doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2023, 2023 Smart City Symposium Prague, New York, IEEE Press), p. 1-6), ISBN 979-8-3503-2162-3, ISSN 2691-3666
Anotace:
The paper deals with the analysis of histograms of discrete data collected in questionnaires obtained for individual realizations of the target variable. The main aim of the analysis isto explore the influence of combinations of explanatory variables, represented by responses to the questionnaire, on the behavior of the target variable of the questionnaire. In this paper, an automated approach to histogram comparison is proposed based on coding combinations of data and detecting significant differences in frequencies using the Marascuilo procedure. This is the main contribution of the paper. The approach is validated using a simulated questionnaire in which respondents answered regarding their intention to purchase an electric vehicle subject to finance, leasing, and charging availability, as well as their driving style. The results of the experiments are demonstrated.
DOI:
10.1109/SCSP58044.2023.10146233
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Tetiana Reznychenko
Publikováno:
2023, Proceedings of the The 12th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) IDAACS’2023, Dortmund, IEEE), p. 51-56), ISBN 979-8-3503-5804-9, ISSN 2770-4254
Anotace:
The paper considers the problem of online prediction of a count variable based on real-time explanatory data of mixed count and categorical nature. The presented solution is based on (i) recursive Bayesian estimation of a mixture model of Poisson-distributed explanatory counts, using the categorical explanatory variable as a measurable pointer of the mixture, (ii) construction of a mixture of local Poisson regressions on the clustered data, and (iii) use of the pre-estimated mixtures for online prediction of the target count using actual measured explanatory data. The latter is one of the main contributions of the proposed approach. In addition, the dynamic model of the categorical explanatory variable preserves the functionality of the algorithm in case of its measurement failure. The experiments with simulations and real data report lower prediction errors compared to theoretical counterparts.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Ing. Jakub Steiner; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2023, Proceedings of the 36th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GNSS+ 2023), Manassas, VA, The Institute of Navigation (ION)), p. 4145-4152), ISBN 978-0-936406-35-0, ISSN 2331-5954
Anotace:
The growing dependence of critical infrastructure on Global Navigation Satellite Systems (GNSS) as an accurate and reliable positioning, navigation and timing (PNT) source gives rise to the importance of GNSS interference detection. Although jamming detection capabilities are present in the current market, predominately in the form of specialised GNSS interference detectors or GNSS receivers add-ons. These provide a limited coverage area and their implementation into critical infrastructure operations is rather slow. Therefore, this paper focuses on the detection of GNSS interference using widespread Automatic Dependent Surveillance-Broadcast (ADS-B) technology. The research builds upon previous work and addresses some of its limitations by developing a discrete mathematical model for GNSS jamming detection based on ADS-B quality parameters. To develop and validate the model, a series of experiments involving GNSS jamming in live-sky environments were conducted. The controlled experiments enabled close monitoring of the aircraft navigation systems allowing for precise determination of the aircraft’s jammed/unjammed status. Approximately 75% of the jamming experiment data was used for model development and tuning, while the remaining 25% was reserved for evaluation. The model evaluation leveraging the confusion matrix showed a positive jamming detection rate of over 99% and a false positive jamming detection rate of under 1%. Additionally, the model was tested on ADS-B data from the Atlantic Ocean where no GNSS jamming is expected. Using this data set the model exhibited an under 1% false positive jamming detection rate.
DOI:
10.33012/2023.19383
Typ:
Stať ve sborníku z prestižní konf. (Scopus)

Autoři:
Ing. David Vodák, Ph.D.; Ing. Martin Jacura, Ph.D.; Svoboda, R.; doc. Ing. Ivan Nagy, CSc.; doc. Ing. Lukáš Týfa, Ph.D.
Publikováno:
2023
Anotace:
Nastavení parametrů stavební úpravy železniční trati je velmi složitý a komplexní proces, neboť v jeho průběhu je zpravidla nutné utřídit a prioritizovat velké množství variant a podvariant. Tyto jsou následně ohodnoceny na základě přepravní prognózy a hodnocení ekonomické efektivity a v závěru celého procesu je vybrána vítězná varianta. Celý proces je velkou měrou ovlivněn budoucím využitím stavebně upravené infrastruktury cestujícími, které je predikováno zmíněnou přepravní prognózou. Tato práce si klade za cíl revizi stávajícího přístupu k nastavování parametrů železničních infrastrukturních staveb s důrazem na vztah mezi úpravou a budoucím využitím tratě cestujícími.
Typ:
Disertační práce (PhD)

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2023, Informatics in Control, Automation and Robotics. ICINCO 2021. Lecture Notes in Electrical Engineering, vol 1006, Springer, Cham), p. 163-184), ISBN 978-3-031-26474-0, ISSN 1876-1119
Anotace:
The chapter focuses on the description of the relationship of the count variable and explanatory Gaussian variables. The cluster-based model is proposed, which is constructed on conditionally independent Gaussian clusters captured in real time using recursive algorithms of the Bayesian mixture estimation theory. The resulting model is expected to be used for predicting count data using real time Gaussian observations. The Poisson distribution of the count data is used as a basic model. However, in reality, count data often do not satisfy the Poisson assumption of equal mean and variance. For this case, five cluster-based Poisson-related models of overdispersed data have been studied. The experimental part of the chapter demonstrates a comparison of the prediction accuracy of the considered models with two theoretical counterparts for the case of weak and strong overdispersion with the help of simulations. The paper reports that the most accurate prediction in average has been provided by the cluster-based Generalized Poisson models.
DOI:
10.1007/978-3-031-26474-0_9
Typ:
Kapitola v jiné knize

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2023, Neural Network World, 33 (4), p. 291-315), ISSN 2336-4335
Anotace:
The development of traffic state prediction algorithms embedded in intelligent transportation systems is of great importance for improving traffic conditions for drivers and pedestrians. Despite the large number of prediction methods, existing limitations still confirm the need to find a systematic solution and its adaptation to specific traffic data. This paper focuses on the relationship between traffic flow states in different urban locations, where these states are identified as clusters of traffic counts. Extending the recursive Bayesian mixture estimation theory to the Poisson mixtures, the paper uses the mixture pointers to construct the traffic state prediction model. Using the predictive model, the cluster at the target urban location is predicted based on the traffic counts measured in real time at the explanatory urban location. The main contributions of this study are: (i) recursive identification and prediction of the traffic state at each time instant, (ii) straightforward Poisson mixture initialization, and (iii) systematic theoretical background of the prediction approach. Results of testing the prediction algorithm on real traffic counts are presented.
DOI:
10.14311/NNW.2023.33.017
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
Ing. Tereza Dvořáková; doc. Ing. Peter Vittek, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2022, 2022 New Trends in Civil Aviation (NTCA), Praha, České vysoké učení technické v Praze), p. 63-67), ISBN 978-80-01-06985-1, ISSN 2694-7854
Anotace:
The evolution of airports toward the Smart Airport concept is currently very topical. The Smart Airport concept brings the digitization and new technologies amongst other benefits. This article deals with the impact of smart technologies, implemented to increase the passenger throughput at airport processors, on waiting times in the queue. To enable simulating the impact of various passenger throughputs, a developed generic model, that can be primarily applied to arrival border control at any airport, was used. Based on the simulation results, the difference in the waiting times in the queue depending on different processing times and used technologies can be compared and analyzed. Therefore, the model can also be used to determine the impact of implementation of smart technologies on the passenger flow at the airport. A simulation performed in the model comparing manual, smart and hybrid configurations of the arrival border control is analyzed in this paper.
DOI:
10.23919/NTCA55899.2022.9934165
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
Ing. Šárka Jozová, Ph.D.; doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Likhonina, R.
Publikováno:
2022, Neural Network World, 32 (1), p. 15-41), ISSN 1210-0552
Anotace:
The paper deals with the task of modeling discrete questionnaire data with a reduced dimension of the model. The discrete model dimension is reduced using the construction of local models based on independent binomial mixtures estimated with the help of recursive Bayesian algorithms in the combination with the naive Bayes technique. The main contribution of the paper is a three-phase algorithm of the discrete model dimension reduction, which allows to model high-dimensional questionnaire data with high number of explanatory variables and their possible realizations. The proposed general solution is applied to the traffic accident questionnaire analysis, where it takes the form of the classification of the accident circumstances and prediction of the traffic accident severity using the currently measured discrete data. Results of testing the obtained model on real data and comparison with theoretical counterparts are demonstrated.
DOI:
10.14311/NNW.2022.32.002
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
Ing. Šárka Jozová, Ph.D.; doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2021, Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - ICINCO, Setùbal, SciTePress), p. 641-648), ISBN 978-989-758-522-7, ISSN 2184-2809
Anotace:
This paper aims at presenting the on-line non-iterative form of Bayesian mixture estimation. The model used is composed of a set of sub-models (components) and an estimated pointer variable that currently indicates the active component. The estimation is built on an approximated Bayes rule using weighted measured data. The weights are derived from the so called proximity of measured data entries to individual components. The basis for the generation of the weights are integrated likelihood functions with the inserted point estimates of the component parameters. One of the main advantages of the presented data analysis method is a possibility of a simple incorporation of the available prior knowledge. Simple examples with a programming code as well as results of experiments with real data are demonstrated. The main goal of this paper is to provide clear description of the Bayesian estimation method based on the approximated likelihood functions, called proximities.
DOI:
10.5220/0010508706410648
Typ:
Stať ve sborníku z prestižní konf. (Scopus)

Autoři:
Ing. Šárka Jozová, Ph.D.; Tobiška, J.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2021, Neural Network World, 31 (3), p. 227-238), ISSN 1210-0552
Anotace:
According to the statistics about vehicle accidents, there are many causes such as traffic violations, reduced concentration, micro sleep, hasty aggression, but the most frequent cause of accidents at highways is a carelessness of the driver and violation of keeping a safe distance. Producers of vehicles try to take into account this situation by development of assistance systems which are able to avoid accidents or at least to mitigate its consequences. This urgent situation leaded to the described project of investigation of behavior of drivers in dangerous situations occurring in vehicle driving. The research is to help in solution of the present unsatisfactory situation in driving accidents. The developed decisionmaking algorithm of detection serious driving situations that can lead to accidents was tested in the laboratory of driving simulators in FTS CTU, Prague. The data for its testing resembled highway traffic.
DOI:
10.14311/NNW.2021.31.012
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
Jonáková, L.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2021, Neural Network World, 31 (2), p. 89-107), ISSN 1210-0552
Anotace:
This study reflects a unique task with significant business potential, on the edge of the wholesale and retail power market, i.e., optimization of power derivatives purchase strategy of retail customers. Even though the definition of the task as well as initial assumptions may be highly complex, essentially, the purpose of this study can be narrowed down to the estimation of buying signals. The price signals are estimated with the use of machine learning techniques, i.e., one-, two- and three-layer perceptron with supervised learning as well as long short-term memory network, which allow modelling of highly complex functional relationships, and with the use of relative strength index, i.e., momentum technical indicator, which on the contrary allows higher flexibility in terms of parameters adjustment as well as easier results interpretation. Thereafter, performance of these methods is compared and evaluated against the established benchmark.
DOI:
10.14311/NNW.2021.31.005
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Petrouš, M.
Publikováno:
2021, Proceedings of the 18th International Conference on Informatics in Control, Automation and Robotics - ICINCO, Setùbal, SciTePress), p. 600-608), ISBN 978-989-758-522-7, ISSN 2184-2809
Anotace:
The paper deals with predicting a discrete target variable described by the Poisson distribution based on the discretized Gaussian explanatory data under condition of the multimodality of a system observed. The discretization is performed using the recursive mixture-based clustering algorithms under Bayesian methodology. The proposed approach allows to estimate the Gaussian and Poisson models existing for each discretization interval of explanatory data and use them for the prediction. The main contributions of the approach include: (i) modeling the Poisson variable based on the cluster analysis of explanatory continuous data, (ii) the discretization approach based on recursive mixture estimation theory, (iii) the online prediction of the Poisson variable based on available Gaussian data discretized in real time. Results of illustrative experiments and comparison with the Poisson regression is demonstrated.
DOI:
10.5220/0010575006000608
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Ing. Šárka Jozová, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2021, 2021 Smart City Symposium Prague, Piscataway, IEEE Signal Processing Society), ISBN 9780738131580
Anotace:
Data analysis is very important tool for acquiring information about object of our interest. It involves a lot of various methods, mainly from the area of data mining or statistical analysis. However, most of these methods aim at continuous data. In real applications, especially in the field of Smart Cities, questionnaires are a frequent source of data. They are mainly a source of discrete data. As commonly used data analysis methods, such as regression analysis, naturally work with continuous data, complications can occur. However, the linear regression analysis can be carefully used to to analyze discrete data, but carefully.The paper wants to give a warning before a direct mindless use of regression analysis for discrete data, especially when the independent variables are nominal. Also some ways how to modify values of the independent variables to achieve sensible results with linear regression applied to measured discrete data from the Smart City area are sketched.
DOI:
10.1109/SCSP52043.2021.9447393
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Ing. Šárka Jozová, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2020, 2020 Smart City Symposium Prague, New York, IEEE Press), ISBN 978-1-7281-6821-0
Anotace:
Data analysis is an important method for obtaining information which is useful in many projects such as e.g. Smart Cities. Common data sources are questionnaires, their output mainly purveys discrete data. The most common description of discrete data is through categorical models. These models have several advantages such as flexibility but there are also disadvantages such as a huge dimension of the table expressing this distribution for more variables and values and their overparametrization. The aim of this paper is to replace the categorical distribution by another discrete distribution with a lower number of parameters while maintaining the model quality. Binomial distribution was chosen a suitable one because it is determined only by one parameter and this parameter allows to shape the probability function of binomial distribution well. The output of the paper is the presented model of mixture with binomial components. The suggested estimation algorithms are tested on real traffic data.
DOI:
10.1109/SCSP49987.2020.9133938
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Ing. Šárka Jozová, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2020, Automa, 26 (1), p. 26-31), ISSN 1210-9592
Anotace:
Článek se zabývá modelováním diskrétních dopravních dat pomocí binomického, geometrického, Poissonova a rovnoměrného rozdělení.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Vlčková, D.
Publikováno:
2019, METRON, 77 (3), p. 253-270), ISSN 0026-1424
Anotace:
The paper focuses on a problem of comparing clusterings with the same number of clusters obtained as a result of using different clustering algorithms. It proposes a method of the evaluation of the agreement of clusterings based on the combination of the Cohen's kappa statistic and the normalized mutual information. The main contributions of the proposed approach are: (i) the reliable use in practice in the case of a small fixed number of clusters, (ii) the suitability to comparing clusterings with a higher number of clusters in contrast with the original statistics, (iii) the independence on size of the data set and shape of clusters. Results of the experimental validation of the proposed statistic using both simulations and real data sets as well as the comparison with the theoretical counterparts are demonstrated.
DOI:
10.1007/s40300-019-00162-5
Typ:
Článek v periodiku excerpovaném databází Scopus

Autoři:
Petrouš, M.; doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2019, Proceedings of the 16th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2019), Madeira, SciTePress), p. 617-624), ISBN 978-989-758-380-3
Anotace:
The paper deals with the problem of modeling the passenger demand in the tram transportation network. The passenger demand on the individual tram stops is naturally influenced by the number of boarding and disembarking passengers, whose measuring is expensive and therefore they should be modeled and predicted. A mixture of Poisson components with the dynamic pointer estimated by recursive Bayesian estimation algorithms is used to describe the mentioned variables, while their prediction is solved with the help of the Poisson regression. The main contributions of the presented approach are: (i) the model of the number of boarding and disembarking passengers. (ii) the real-time data incorporation into the model. (iii) the recursive estimation algorithm with the normal approximation of the proximity function. The results of experiments with real data and the comparison with theoretical counterparts are demonstrated.
DOI:
10.5220/0007831306170624
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2019, Informatics in Control, Automation and Robotics. ICINCO 2017. Lecture Notes in Electrical Engineering., Springer, Cham), p. 679-698), ISBN 978-3-030-11292-9, ISSN 1876-1119
Anotace:
The paper provides a practical guide on initialization of the recursive mixture-based clustering of non-negative data. For modeling the non-negative data, mixtures of uniform, exponential, gamma and other distributions can be used. Initialization is known to be an important task for a start of the mixture estimation algorithm. Within the considered recursive approach, the key point of initialization is a choice of initial statistics of the involved prior distributions. The paper describes several initialization techniques for the mentioned types of components that can be beneficial primarily from a practical point of view.
DOI:
10.1007/978-3-030-11292-9_34
Typ:
Kapitola v jiné knize

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2019, Transportation Research Part B: Methodological, 128, p. 254-270), ISSN 0191-2615
Anotace:
This paper deals with the task of modeling the driving style depending on the driving environment. The model of the driving style is represented as a two-layer mixture of normal components describing data with two pointers: outer and inner. The inner pointer indicates the actual driving environment categorized as “urban”, “rural” and “highway”. The outer pointer through the determined environment estimates the active driving style from a fuel economy point of view as “low consumption”, “middle consumption” and “high consumption”. All of these driving styles are assumed to exist within each driving environment due to the two-layer model. Parameters of the model and the driving style are estimated online, i.e., while driving using a recursive algorithm under the Bayesian methodology. The main contributions of the presented approach are: (i) the driving style recognition within each of urban, rural and highway environments as well as in the case of switching among them. (ii) the two-layer pointer, which allows us to incorporate the information from continuous data into the model. (iii) the potential use of the data-based model for other measurements using corresponding distributions. The approach was tested using real data.
DOI:
10.1016/j.trb.2019.08.009
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.
Publikováno:
2018, Practical Issues of Intelligent Innovations. Studies in Systems, Decision and Control, Springer, Cham), p. 313-330)
Typ:
Kapitola v jiné knize

Autoři:
doc. Ing. Andrej Lališ, Ph.D.; doc. Ing. Bc. Vladimír Socha, Ph.D.; doc. Ing. Jakub Kraus, Ph.D.; doc. Ing. Ivan Nagy, CSc.; Licu, A.
Publikováno:
2018, IEEE Aerospace Conference Proceedings, IEEE Xplore), p. 1-8), ISBN 978-1-5386-2014-4, ISSN 1095-323X
Anotace:
This paper deals with safety performance predictions in the aviation, which address the long-term global efforts to achieve predictive risk management by the year 2028. Predictive risk management regards timely and accurate detection of risk, well before some incident or accident takes place so that effective control actions can be provided. To assure achieving such diagnosis, it is necessary that mathematically well-founded predictions will become part of existing safety management systems with the capability to predict key performance indicators. From current safety metrics and with respect to the data available in the aviation, overall safety performance was selected as suitable candidate for predictions. To obtain the performance signal, Aerospace Performance Factor methodology was utilized. Due to confidentiality restrictions with regard to aviation safety data, this study relies on public data sets from the domain of European Air Traffic Management. Dedicated resampling method was used to fill in the gaps of real data sets by transforming expert knowledge into mathematical functions. This enabled the possibility to build and test mathematical models for predicting safety performance. Because the identified data sources included some data, which are not necessary for computing safety performance but relevant in its context, conditional forecasts were made possible. With respect to this, the goal of this paper was to research and evaluate possibilities for both conditional and unconditional forecasts in the context of future risk management. Time-series analysis of the computed safety performance was conducted using ordinary least squares and maximum likelihood estimation. Each of the methodology led to different mathematical model and different predictions. Specific aspects of each methodology were identified.
DOI:
10.1109/AERO.2018.8396648
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
Urbaniec, K.; Šimůnek, M.; doc. Ing. Ivan Nagy, CSc.; Ing. Jindřich Borka, Ph.D.; Ing. Milan Sliacky, Ph.D.
Publikováno:
2018, 2018 Smart City Symposium Prague, New York, IEEE Press), p. 1-6), ISBN 978-1-5386-5017-2
Anotace:
In this paper we perceive data analysis with empirical probability functions as a data mining method. We propose a way to carry out this type of analysis by employing the LISp-Miner system, namely the CF-Miner procedure and pattern difference quantifiers. In order to confirm that LISp-Miner is a suitable tool for this purpose, we briefly present both methods and then show their equivalence. We do this by providing theoretical description which we then support by analysing a small set of data concerning traffic accidents with methods and comparing results. Afterwards we provide an example of analysis of a full data set concerning rail tickets sold at selected stations in 2014. We show that by considering “difference histograms” it is possible to identify remarkable dissimilarities in histograms of time of ticket sale that would not be found otherwise. Both analyses confirms that the method we propose can provide new and interesting results even if the data has been already analysed.
DOI:
10.1109/SCSP.2018.8402674
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
Ing. Miroslav Vaniš, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2018, Young Transportation Engineers Conference 2018, Praha, Fakulta dopravní), p. 53-61), ISBN 978-80-01-06464-1
Anotace:
Bayesian networks are one of the most suitable tools for traffic accident data analysis. A well-designed and trained Bayesian network is the first assumption for obtaining good results. Two sources of information can be used for this purpose. They are information extracted from measured historical data and also information specified by an expert. The latter one can also involve some generally known rules or knowledge based on traffic regulations or safety rules. Mostly, only one of these sources of information is used. After training the network can be evaluated with standard methods based on likelihood or prediction error evaluation. The goal of this paper is to show that if two Bayesian networks are created, e.g. one from the data and second from the expert knowledge, they can be merged into one which joins the objective information from data with the subjective opinion from expert and which has better evaluation than the original ones.
Typ:
Stať ve sborníku z mezinár. konf. cizojazyčně

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2018, Intuitionistic Fuzziness and Other Intelligent Theories and Their Applications. Studies in Computational Intelligence., Springer, Cham), ISBN 978-3-319-78931-6, ISSN 1860-9503
Anotace:
The initialization is known to be a critical task for running a mixture estimation algorithm. A majority of approaches existing in the literature are related to initialization of the expectation-maximization algorithm widely used in this area. This study focuses on the initialization of the recursive mixture estimation for the case of normal components, where the mentioned methods are not applicable. Its key part is a choice of the initial statistics of normal components.
DOI:
10.1007/978-3-319-78931-6_3
Typ:
Kapitola v jiné knize

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.
Publikováno:
2017, ISBN 978-3-319-64670-1, ISSN 2191-544X
Anotace:
This book provides a general theoretical background for constructing the recursive Bayesian estimation algorithms for mixture models. It collects the recursive algorithms for estimating dynamic mixtures of various distributions and brings them in the unified form, providing a scheme for constructing the estimation algorithm for a mixture of components modeled by distributions with reproducible statistics. It offers the recursive estimation of dynamic mixtures, which are free of iterative processes and close to analytical solutions as much as possible. In addition, these methods can be used online and simultaneously perform learning, which improves their efficiency during estimation. The book includes detailed program codes for solving the presented theoretical tasks. Codes are implemented in the open source platform for engineering computations. The program codes given serve to illustrate the theory and demonstrate the work of the included algorithms.
DOI:
10.1007/978-3-319-64671-8
Typ:
Jiná kniha

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2017, Transportation Research Part C: Emerging Technologies, p. 23-36), ISSN 0968-090X
Anotace:
The paper focuses on a task of stochastic modeling the driving style and its online estimation while driving. The driving style is modeled by means of a mixture model with normal and categorical components as well as a data-dependent pointer. The main contributions of the presented approach are: (i) the online estimation of the driving style while driving, taking into account data up to the current time instant; (ii) the joint model for continuous and discrete data measured on a vehicle; (iii) the data-dependent model of the driving style conditioned by the values of fuel consumption; (iv) the use of the model both for detection of clusters according to the driving style and prediction of the fuel consumption along with other variables; and (v) the universal modeling with the help of mixtures, which allows us to use different combinations of components and pointer models as well as to specify the initialization approach suitable for the considered problem.
DOI:
10.1016/j.trc.2017.11.001
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Petrouš, M.
Publikováno:
2017, Intelligent Systems and Informatics (SISY), 2017 IEEE 15th International Symposium on, Budapest, IEEE Hungary Section, University Obuda), ISBN 978-1-5386-3855-2, ISSN 1949-0488
Anotace:
This paper deals with a modeling of data by several mixtures of different distributions within a task of clustering. This issue can be required from a practical point of view, e.g., for a multi-modal system, which generates measurements described by different distributions. The approach is based on the partition of the data on several parts, the factorization of the joint probability density function according to these parts and the estimation of each conditional mixture separately. Due to the data-based construction of the general model from the estimated components, the most suitable combination of the components is used at each time instant.
DOI:
10.1109/SISY.2017.8080574
Typ:
Stať ve sborníku z lokální konf.

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Ing. Pavla Pecherková, Ph.D.; Likhonina, R.
Publikováno:
2017, Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics, Madeira, SciTePress), ISBN 978-989-758-263-9
Anotace:
The paper deals with a task of initialization of the recursive mixture estimation for the case of uniform components. This task is significant as a part of mixture-based clustering, where data clusters are described by the uniform distributions. The issue is extensively explored for normal components. However, sometimes the assumption of normality is not suitable or limits potential application areas (e.g., in the case of data with fixed bounds). The use of uniform components can be beneficial for these cases. Initialization is always a critical task of the mixture estimation. Within the considered recursive estimation algorithm the key point of its initialization is a choice of initial statistics of components. The paper explores several initialization approaches and compares results of clustering with a theoretical counterpart. Experiments with real data are demonstrated.
DOI:
10.5220/0006417104490458
Typ:
Stať ve sborníku z lokální konf.

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Petrouš, M.
Publikováno:
2017, Proceedings of International Conference on Intelligent Informatics and BioMedical Sciences ICIIBMS 2017, Okinawa, Okinawa Institute of Science and Technology), p. 63-70), ISBN 978-1-5090-6664-3, ISSN 2189-8723
Anotace:
The paper deals with the mixture-based clustering of anonymized data of patients with leukemia. The presented clustering algorithm is based on the recursive Bayesian mixture estimation for the case of exponential components and the data-dependent dynamic pointer model. The main contribution of the paper is the online performance of clustering, which allows us to actualize the statistics of components and the pointer model with each new measurement. Results of the application of the algorithm to the clustering of hematological data are demonstrated and compared with theoretical counterparts.
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
Procházková, D.; doc. Ing. Ivan Nagy, CSc.; Kertis, T.
Publikováno:
2016, Sborník příspěvků konference Young Transportation Engineers Conference 2016, Praha, České vysoké učení technické v Praze), p. 1-10), ISBN 978-80-01-06016-2
Anotace:
Statistická směs je moderní metoda teorie stochastických systémů. Předkládaná práce zavádí metodu pro analýzu seismických dat, tj. najít místa s největším výskytem epicenter zemětřesení ve střední Evropě na základě historických seizmických dat. Práce je založena na teoretické znalosti statistických směsí a skutečných údajích o seismické aktivitě ve střední Evropě. Článek obsahuje popis přípravy dat pro použití uvedené metody s definovaným algoritmem. Výsledky práce jsou plošná hustota pravděpodobnosti výskytu možných epicenter zemětřesení a posouzení míry korelace s reálnými výsledky.
Typ:
Stať ve sborníku z mezinár. konf. česky

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Ing. Pavla Pecherková, Ph.D.
Publikováno:
2016, Proceedings of the 13th International Conference on Informatics in Control, Automation and Robotics (ICINCO 2016), Porto, SciTePress - Science and Technology Publications), ISBN 978-989-758-198-4
Anotace:
Classification is one of the frequently demanded tasks in data analysis. There exists a series of approaches in this area. This paper is oriented towards classification using the mixture model estimation, which is based on detection of density clusters in the data space and fitting the component models to them. A chosen function of proximity of the actually measured data to individual mixture components and the component shape play a significant role in solving the mixture-based classification task. This paper considers definitions of the proximity for several types of distributions describing the mixture components and compares their properties with respect to speed and quality of the resulting estimation interpreted as a classification task. Normal, exponential and uniform distributions as the most important models used for describing both Gaussian and non-Gaussian data are considered. Illustrative experiments with results of the comparison are provided.
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Mlynářová, T.
Publikováno:
2016, 2016 IEEE 8th International Conference on Intelligent Systems (IS), Sofia, IEEE), ISBN 978-1-5090-1354-8
Anotace:
Initialization is an extremely important part of the mixture estimation process. There exists a series of initialization approaches in the literature concerning the mixture initialization. However, the majority of them is directed at initialization of the expectation-maximization algorithm widely used in this area. This paper focuses on the initialization of the mixture estimation with normal components based on the recursive statistics update of involved distributions, where the mentioned methods are not suitable. Its key part is the choice of the initial statistics. The paper describes several relatively simple initialization techniques primarily based on processing the prior data. The experimental part of the paper represents results of validation on real data.
DOI:
10.1109/IS.2016.7737439
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
Ing. Pavla Pecherková, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2016, 2016 Smart Cities Symposium Prague (SCSP), New York, IEEE Press), ISBN 978-1-5090-1116-2
Anotace:
This paper deals with problem of analysis of traffic data. A traffic network has several types of roads: historical centre, peripherals, arterial roads, etc. They have specific properties. For a traffic analysis, large amounts of data are needed. Some traffic data are difficult to obtain due to their rare occurrence. Typical example is the investigation of traffic accidents. In these cases, data from other similar roads can be used. In such cases, an expert intervention added to the general analysis is very important. In this paper, the logistic regression with two types of expert intervention is briefly introduced. The performance of these methods is demonstrated on examples concerning seriousness of traffic accidents.
DOI:
10.1109/SCSP.2016.7501032
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Mlynářová, T.
Publikováno:
2016, 2016 IEEE 8th International Conference on Intelligent Systems (IS), Sofia, IEEE), p. 265-271), ISBN 978-1-5090-1354-8
Anotace:
This paper deals with clustering non-gaussian data with fixed bounds. It considers the problem using recursive mixture estimation algorithms under the Bayesian methodology. Such a solution is often desired in areas, where the assumption of normality of modeled data is rather questionable and brings a series of limitations (e.g., non-negative, bounded data, etc.). Here for modeling the data a mixture of uniform distributions is taken, where individual clusters are described by mixture components. For the on-line detection of clusters of measured bounded data, the paper proposes a mixture estimation algorithm based on (i) the update of reproducible statistics of uniform components; (ii) the heuristic initialization via the method of moments; (iii) the non-trivial adaptive forgetting technique; (iv) the data-dependent dynamic pointer model. The approach is validated using realistic traffic flow simulations.
DOI:
10.1109/IS.2016.7737431
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.
Publikováno:
2016, Neural Network World, 26 (5), p. 417-437), ISSN 1210-0552
Anotace:
The paper deals with a problem of modeling discrete variables depending on continuous variables. This problem is known as the logistic regression estimated by numerical methods. The paper approaches the problem via the recursive Bayesian estimation of mixture models with the purpose of exploring a possibility of constructing the continuous data dependent switching model that should be estimated on-line. Here the model of the discrete variable dependent on continuous data is represented as the model of the mixture pointer dependent on data from mixture components via their parameters, which switch according to the activity of the components. On-line estimation of the data dependent pointer model has a great potential for tasks of clustering and classification. The specific subproblems include (i) the model parameter estimation both of the pointer and of the components obtained during the learning phase, and (ii) prediction of the pointer value during the testing phase.
DOI:
10.14311/NNW.2016.26.024
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Mlynářová, T.
Publikováno:
2015, Proceedings of the 16th conference of the Applied Stochastic Models and Data Analysis (ASMDA) International Society, Piraeus, University of Piraeus, Greece), p. 727-738)
Anotace:
The presented paper deals with a task of the multi-step prediction with mixture models under Bayesian methodology. The main contribution of the paper is a recursive prediction algorithm for mixtures with the dynamic switching model. The proposed algorithm is based on construction of the weighting vector predicting the active component and its combination with data predictions from components. With the help of illustrative examples the paper compares the results with those obtained for the mixture prediction with the static switching model.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Ing. Pavla Pecherková, Ph.D.; Urbaniec, K.
Publikováno:
2015, 2015 Smart Cities Symposium Prague (SCSP), New York, IEEE Press), ISBN 978-1-4673-6727-1
Anotace:
The paper deals with detection of clusters in data measured on a driven vehicle. Such a clustering aims at distinguishing various driving styles for eco-driving and driver assistance systems. The task is solved with the help of the application of the recursive Bayesian mixture estimation theory. The main contribution of the paper is a demonstration that real measurements with non-linear relations.
DOI:
10.1109/SCSP.2015.7181548
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Mlynářová, T.
Publikováno:
2015, Proceedings of the 2015 IEEE 8th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), Ternopil, Ternopil National Economic University), p. 137-142), ISBN 9781467383615
Anotace:
The paper deals with estimation of a mixture of normal and exponential distributions with the dynamic model of their switching. A separate estimation of normal or exponential mixtures is solved by various approaches in many papers over the world. However, in some application areas, data are of such a nature that they should be described by a combination of exponential and normal models. The paper proposes a recursive Bayesian algorithm of estimation of such a mixture based on continuously measured data. Specific tasks the paper solves are: (i) parameter estimation of both the types of components; (ii) parameter estimation of the dynamic switching model and (iii) detection of the currently active component. Results of experiments with real data are demonstrated.
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2014, Transportation Research Part C: Emerging Technologies, 44, p. 253-264), ISSN 0968-090X
Anotace:
The paper describes application of data-based Bayesian approach to model identification and control problems in the field of fuel consumption optimization for conventional vehicles. The main contributions of the presented approach are: (i) analysis of data measured on a driven vehicle; (ii) data-based model construction, its real-time estimation and adaptation; (iii) control criterion using simultaneously setpoints for fuel consumption and speed; (iv) universal recursive Bayesian algorithms of estimation and control implemented as semi-automatic eco-driving system. Experiments with real data report reduction in fuel consumption.
DOI:
10.1016/j.trc.2014.04.009
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Pavelková, L.; Mlynářová, T.
Publikováno:
2013, Proceedings of the 11th IFAC International Workshop on Adaptation and Learning in Control and Signal Processingn, Caen, IFAC), p. 305-310), ISBN 978-3-902823-37-3
Anotace:
This paper presents automatic fuel consumption optimization with simultaneous keeping the recommended vehicle's speed. These tasks are closely related since a simple minimization of fuel consumption leads to stopping a vehicle. The proposed ``double'' optimization is performed online using combination of two controllers. The first of them is based on fully probabilistic design (FPD) under Bayesian methodology. It optimizes the ``driver-vehicle'' closed loop with the aim to save fuel and keep the recommended speed, using externally given setpoints. Optimized values serve as setpoints for PID controller, which provides necessary setpoint tracking.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.; Ing. Pavla Pecherková, Ph.D.; Mgr. Pavel Provinský, Ph.D.
Publikováno:
2013, 20th Anniversary of the Faculty of Transportation Sciences, Czech Technical University in Prague - Selected Papers, Praha, České vysoké učení technické v Praze, Fakulta dopravní), p. 9-13), ISBN 978-80-01-05320-1
Anotace:
This paper deals with an automatic vehicle control system that on condition of adhering to safety rules and road laws minimizes fuel consumption. The control is calculated in order to minimize fuel consumpton with regards to approximate adherence to given recommended speed. This control is subordinated by a logic block which specifically helps to adhere to road safety and road laws.
Typ:
Stať ve sborníku z fakultní konference cizojazyčně

Autoři:
Štecha, R.; Šulc, J.; doc. Ing. Ivan Nagy, CSc.; prof. Ing. Věra Voštová, CSc.
Publikováno:
2013, Interdisciplinární mezinárodní vědecká konference doktorandů a odborných asistentů QUAERE 2013, Hradec Králové, Magnanimitas), ISBN 978-80-905243-7-8
Anotace:
Flight safety together with demands on effective and well-ordered air traffic flow is an essential requirement of modern society. Flight safety depends on proper human and machine operations. The paper is focused on the impact of objective and subjective aspects on human factors in the Air Traffic Control environment. Special interest is paid to the influence of day-time and season period, character of air traffic, aircraft movement phase, meteorological conditions, Moon-phases, flight-release conditions and air traffic intensity in particular airspace. Data of 981 air traffic occurrences records were gathered during the period 2000 - 2012 in Czech Republic, Great Britain, Canada and United States, respectively.
Typ:
Stať ve sborníku z mezinár. konf. cizojazyčně

Autoři:
Štecha, R.; Šulc, J.; doc. Ing. Ivan Nagy, CSc.; prof. Ing. Věra Voštová, CSc.
Publikováno:
2013, Mezinárodní Masarykova konference pro doktorandy a mladé vědecké pracovníky 2013, Hradec Králové, Magnanimitas), ISBN 978-80-87952-00-9
Anotace:
Bezpečnost v řízení letového provozu závisí zejména na správném rozhodování řídících letového provozu. Veškerá rozhodnutí řídících jsou ovlivňována celou řadou objektivních a subjektivních faktorů – lidských činitelů. Některé z nich lze ovlivnit nebo využít, jiné nikoli. Objem a intenzita letového provozu setrvale rostou a jejich omezování nedostatečnou kapacitou uspořádání letového provozu (řízení nevyjímaje) není žádoucí ani přijatelné. Závěry výzkumu, které jsou prezentovány v tomto článku, vycházejí z retrospektivní analýzy leteckých nehod a incidentů (událostí) zaviněných orgány řízení letového provozu, k nimž došlo v letech 2000 – 2012. Byl zjištěn a klasifikován vliv jednotlivých faktorů, které provázely výskyt událostí v letovém provozu podle jejich závažnosti. Na základě výsledků statistické analýzy i matematického modelování byly vyhodnoceny jako nejdůležitější faktory časové, provozní, prostorové a meteorologické. Je patrné, že největší prostor pro využití a ovlivnění představují organizační a režimová opatření. K hlavním organizačním opatřením se řadí zejména způsoby plánování služeb a odpočinku řídících letového provozu. Režimová opatření spočívají ve vytvoření kvalitních podmínek pro práci řídících.
Typ:
Stať ve sborníku z mezinár. konf. česky

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.
Publikováno:
2013, Applied Mathematical Modelling, 37 (24), p. 9970-9984), ISSN 0307-904X
Anotace:
The paper deals with estimation of mixture with state state space components and static discrete model for switching.
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
Štecha, R.; doc. Ing. Ivan Nagy, CSc.; prof. Ing. Věra Voštová, CSc.
Publikováno:
2013, Proceedings of the International Scientific Conference Modern Safety Technologies in Transportation, Košice, PERPETIS S.R.O.), p. 252-258), ISBN 978-80-971432-0-6, ISSN 1338-5232
Anotace:
Air Traffic Controllers (ATCOs) play a crucial role in the Air Traffic Control which is considered as the most visible and flexible part of the Air Traffic Management (ATM) system. Despite all automated process and tools for ATCOs decision-making support the control of the airspace and air traffic and problem solving will remain in hands of the controllers. No system is 100% reliable and accurate and any human-provided actions can be fully supplied by machines. All decisions made by a controller are influenced by huge number of factors. Their impact varies on each person individually and it is impossible to distinguish which factor has the most significant influence on flight safety and which the less. The first part of this paper is focused on impact of objective and subjective aspects on human factors in the air traffic control. The special interest is concentrated on influence of day-time and season, air traffic type, aircraft movement phase, meteorological conditions, flight-release conditions, air traffic intensity in particular airspace. The second part concentrates of combinations of risk factors and a construction of their model. Data presented in this article contains 981 air traffic control involved occurrences records covering 2000 – 2012 years in the Czech Republic, Great Britain, Canada and United States of America.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Štecha, R.; Šulc, J.; prof. Ing. Věra Voštová, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2013, International Conference on Air Transport 2013, Žilina, EDIS), p. 132-136), ISBN 978-80-554-0776-0
Anotace:
Air Traffic Controllers play a crucial role in Air Traffic Control, which is considered the most visible and flexible part of the Air Traffic Management (ATM) system. All decisions made by controllers are influenced by a huge number of factors, both objective and subjective. Some studies have established a model of the risks in ATM, but none have combined statistics and modeling principles in a Bayesian approach. The study is based on a wide retrospective analysis of the air traffic occurrences where controllers were involved. The data presented in this article comprise 981 air traffic control-involved occurrences records covering the years 2000 – 2012 in the Czech Republic, Great Britain, Canada and the United States of America. We analyzed the individual roles of all known factors contributing to the occurrences. Occurrences were classified as air accidents and incidents of serious, major, significant or no safety effects. The most significant and correlating variables were used for the discrete risk model. Our results did not confirm the impact of adverse meteorological conditions or high air traffic intensity on the number of ATC involved occurrences. On the contrary, the majority of reported accidents occurred in ideal weather and in low-density traffic. Most occurrences were recorded in the vicinity of the airports, during aircraft approach maneuvers and landing. The most critical time for the occurrences is between 04:00 and 07:59 a.m. Our discrete risk model suggests the combination of time of day, meteorological conditions, type of flight and aircraft (vortex) category as the most relevant.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Mlynářová, T.
Publikováno:
2013, Proceedings of 16th International IEEE Conference on Intelligent Transportation Systems, Red Hook, NY, Curran Associates), p. 2088-2093), ISBN 978-1-4799-2914-6, ISSN 2153-0009
Anotace:
The paper deals with fuel consumption optimization under condition of keeping the recommended speed. The presented approach is based on data currently measured on a driven vehicle and on external observations. Using adaptive optimal control algorithms under Bayesian methodology, a compromise between fuel consumption minimization and keeping the recommended speed is reached. Research is performed in collaboration with Skoda Auto (www.skoda-auto.com).
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Ing. Pavla Pecherková, Ph.D.
Publikováno:
2013, Proceedings of the 11th European Transport Congress, Praha, České vysoké učení technické v Praze, Fakulta dopravní), p. 178-184), ISBN 978-80-01-05321-8
Anotace:
The paper presents actual results of the project oriented at development of algorithms for the advising system for eco-driving. The paper discusses the experiments for validation of the control algorithm used for the fuel consumption optimization problem within the project.
Typ:
Stať ve sborníku z mezinár. konf. cizojazyčně

Autoři:
Štecha, R.; Šulc, J.; doc. Ing. Ivan Nagy, CSc.; prof. Ing. Věra Voštová, CSc.
Publikováno:
2013, Sborník přednášek z Mezinárodní konference hyperbarické a letecké medicíny k 60. výročí založení Ústavu leteckého zdravotnictví Praha 20. kongres České společnosti hyperbarické a letecké medicíny ČLS JEP, Ostrava, Ostravská univerzita v Ostravě), p. 100-104), ISBN 978-80-7464-260-9
Anotace:
Zajištění mnoha činností nezbytných pro současný život lidí vyžaduje nepřetržitý pracovní režim 24 hodin denně 7 dní v týdnu (24/7). Pracovníci se přizpůsobují tomuto pracovnímu režimu různými způsoby v závislosti na komplexní interakci mezi endogenními faktory (věk, pohlaví, osobnost atd.) a exogenními faktory (směnný provoz, plněné úkoly, sociální a životní podmínky atd.). V minulosti bylo provedeno několik studií za účelem identifikovat individuální rozdíly (obzvláště pak v cirkadiánní typologii), které mohou modulovat adaptaci na práci ve směnném provozu, protože nepřímo ovlivňují výkonnost. Ukazuje se, že lidé typu „sova“ se změnám ve spánkovém režimu a tedy i změnám vyplývajícím z převráceného pracovního režimu přizpůsobují snadněji než „skřivani“. Řídící letového provozu patří rovněž do skupiny lidí, jejichž pracovní činnost probíhá nepřetržitě. Tyto profese jsou tedy vystaveny potenciálnímu negativnímu vlivu špatně stanoveného rytmu směn na cirkadiánní rytmus a tudíž na úroveň výkonnosti. V prostředí řízení letového provozu je jedním z měřítek kvality práce bezpečnost letového provozu, která je naprosto zásadní. Předmětem článku je sledování vlivu času, jakožto jedné z komponenty lidského činitele, na bezpečnost v řízení letového provozu.
Typ:
Stať ve sborníku z mezinár. konf. česky

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Pavelková, L.
Publikováno:
2012, Proceedings of the 16th IFAC Symposium on System Identification, Laxenburg, IFAC), p. 751-756), ISBN 978-3-902823-06-9, ISSN 1474-6670
Anotace:
The paper deals with a problem of fuel consumption optimization. Solutions existing in this field are mainly based on the various conceptual approaches such as hybrid and electric vehicles. However, it leads to high initial cost of a vehicle. The approach presented in this paper aims at conventional vehicles and is based on recursive algorithms of system identification and adaptive quadratic optimal control under Bayesian methodology. Experiments with real data measured on a driven vehicle are provided.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2012, Computers and Chemical Engineering, 10 (36), p. 294-300), ISSN 0098-1354
Anotace:
Online state prediction and fault detection are typical tasks in the chemical industry. In practice it often happens that some variables, important and critical for quality control, cannot be measured online due to such restrictions as cost and reliability. An uncertainty existing in real systems allows to use a probabilistic approach to online state estimation. Such an approach is proposed in this paper. Different types of information appearing in an online diagnostic system are processed via combination of algorithms subject to probability distributions. This combination of algorithms is presented as a decomposed version of Bayesian filtering. In this paper, the proposed solution is specialized for a system with mixed both continuous and discrete-valued measurements and unobserved variables.
DOI:
10.1016/j.compchemeng.2011.09.004
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
Dedecius, K.D.; doc. Ing. Ivan Nagy, CSc.; Kárný, M.K.
Publikováno:
2012, International Journal of Adaptive Control and Signal Processing, 26 (1), p. 1-12), ISSN 0890-6327
Anotace:
This paper concerns the Bayesian tracking of slowly varying parameters of a linear stochastic regression model. The modelled and predicted system output is assumed to possess time-varying mean value, whereas its dynamics are relatively stable. The proposed estimation method models the system output mean value by time-varying offset. It formulates three extreme hypotheses on model parameters' variability: (i) no parameter varies; (ii) all parameters vary; and (iii) the offset varies. The Bayesian paradigm then provides a mixture as posterior distribution, which is appropriately projected to a feasible class. Exponential forgetting at second hypotheses level allows tracking of slow variations of respective hypotheses.
DOI:
10.1002/acs.1270
Typ:
Článek v odborném recenzovaném periodiku

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2012, Applied Mathematical Modelling, 36 (4), p. 1347-1356), ISSN 0307-904X
Anotace:
The paper deals with recursive state estimation for hybrid systems. An unobservable state of such systems is changed both in a continuous and a discrete way. Fast and efficient online estimation of hybrid system state is desired in many application areas. The presented paper proposes to look at this problem via Bayesian filtering in the factorized (decomposed) form. General recursive solution is proposed as the probability density function, updated entry-wise. The paper summarizes general factorized filter specialized for (i) normal state-space models; (ii) multinomial state-space models with discrete observations; and (iii) hybrid systems. Illustrative experiments and comparison with one of the counterparts are provided.
DOI:
10.1016/j.apm.2011.08.042
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Pavelková, L.; Mlynářová, T.
Publikováno:
2012, Proceedings of the IASTED International Conference on Engineering and Applied Science, Calgary, IASTED), p. 100-107), ISBN 978-0-88986-941-7
Anotace:
The presented paper deals with a problem of fuel consumption optimization. Today's automotive industry solves this problem mainly via various conceptual approaches (hybrid and electric vehicles). However, it leads to high initial cost of a vehicle. This paper focuses on fuel economy for conventional vehicles. For this aim, recursive algorithms of adaptive optimal quadratic control under Bayesian methodology are used. A stochastic servo problem, including set-point tracking, is a part of the considered adaptive control design. In this paper, fuel consumption and speed of a driven vehicle are the controlled variables, where the first one is to be optimized and the second one is pushed to track its set-point. This set-point is a recommended road-dependent speed. Experiments with real data measured on a driven vehicle are provided.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Kárný, M.; Mlynářová, T.
Publikováno:
2011, International Journal of Adaptive Control and Signal Processing, 9 (25), p. 765-787), ISSN 0890-6327
Anotace:
The paper introduces an alforithm for estimation of dynamic mixture models. A new featur of the proposed algorithm is the ability to consider a dynamic form not only for component models but also for the pointer model, which describes the activities of the mixture components in time.
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Kárný, M.
Publikováno:
2011, Kybernetika, 4 (47), p. 572-594), ISSN 0023-5954
Anotace:
Probabilistic mixture provide flexible "universal" approximation of probability density functions. Their wide use is enabled by the availability of a range of efficient estimation algorithms. Among them, quasi-Bayesian estimation plays a prominent role as it runs "naturally" in one-pass mode. This is important in on-line applications and/or extensive databases. It even copes with dynamic nature of components forming the mixture. However, the quasi-Bayesian estimation relies on mixing via constant component weights. Thus, mixtures with dynamic components and dynamic transitions between them are not supported. The present paper fills this gap. For the sake of simplicity and to give a better insight into the task, the paper considers mixtures with known components. A general case with unknown components will be presented soon.
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Ivan Nagy, CSc.; doc. Ing. Evženie Uglickich, CSc.; Mlynářová, T.
Publikováno:
2011, IDAACS'2011 - Proceedings of the 6th IEEE International Cnonference on Intelligent Data Acquisition and Advanced Computing Systems, Prague, IEEE, THEY, CTU), p. 527-531), ISBN 978-1-4577-1423-8
Anotace:
Many variousal gorithms are developed forstate estimation ofdynamic switching systems. Itis not a straight for wardtask to choosethe most suitableone. This paperdeal swith testing ofstateestimation via two well know napproaches: recursiveestimation with finitemix turesand iterative technique with hidden Markov models. A discussion ofcomparisonof these online and of flinecoun terpartsi softrueinterest. The paper descri besex periment sproviding a comparisonof these methods.
Typ:
Stať ve sborníku z prestižní konf.

Autoři:
Dedecius, K.D.; doc. Ing. Ivan Nagy, CSc.; Hofman, R.
Publikováno:
2011, CTU Workshop 2011, Praha, České vysoké učení technické v Praze), p. 1-11)
Anotace:
Computing the future road traffic intensities in urbyn and suburban areas is considered inthis paper. The statistical properties of the traffic flow advocate the use a low-order lin-ear autoregressive models, in which the previous intensities determine the following ones. To achieve adaptivity, the Bayesian modelling framework was chosen. The regression coefficients are considered random, hence they are modelled using a suitable distribution. A significant improvement of the overall modelling performance is further reached with techniques allowing the parametres vary by modification of their distiburion. We present the partial forgetting method, allowing to individually track the parameters even in the case of their different variability rate.
Typ:
Stať ve sborníku Workshop ČVUT

Autoři:
doc. Ing. Evženie Uglickich, CSc.; doc. Ing. Ivan Nagy, CSc.; Dungl, M.
Publikováno:
2011, Proceedings of the 14th Applied Stochastic Models and Data Analysis Conference, Roma, Universita di Roma), p. 1299-1306), ISBN 978-88-467-3045-9
Anotace:
The paper deals with online state estimation for dynamic hybrid systems with mixed continuous and discrete states. The proposed solution is based on a decomposed version of the state-space model and Bayesian filtering. Specialization to Gaussian linear dynmic and multinomial state-space models is described. Experiments with real data ilustrating the presented approch are provided.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Ing. Jan Krčál, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2010, Latest Trends on Communication & Information Technology, New York, WSEAS Press), p. 101-104), ISBN 978-960-474-207-3, ISSN 1792-4316
Anotace:
Computation of traffic management is dependent upon a model, which determines the headway of vehicles in the intersection upon a green signal "go" - this is called a departure model. Hitherto used models have been based solely on individual observations and quest for an appropriate artificial function, which would respect these observations. However, such models turn out to be inaccurate and their application in transportation management is problematic - they are only applicable for those intersections, on which the data was collected at a given time, without relationship to other variables impacting departure of vehicles (such as geometrical order, departure direction, road angle etc.). The article describes a lay out of a departure model by creating a new complex mathematical apparatus.
Typ:
Stať ve sborníku z lokální konf.

Autoři:
Menglerová, K.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2010, Automa, 16 (3), p. 42-45), ISSN 1210-9592
Anotace:
Tento článek o dynamice vozidla, které se pohybuje bezprostředně za vozidlem (prvním z dvojice vozidel) jedoucím konstantní rychlostí po přímočaré vodorovné trajektorii. Řízení vozidla je modelováno podmínkou dodržování bezpečné vzdálenosti řízeného vozidla za vozidlem jedoucím před ním. Tato podmínka modeluje chování řidiče a jeho subjektivní hodnocení dynamiky řízeného vozidla s ohledem na polohu vozidla jedoucího bezprostředně před ním.
Typ:
Článek v periodiku z pozitivního seznamu RVVI česky

Autoři:
Dedecius, K.; doc. Ing. Ivan Nagy, CSc.; Hofman, R.
Publikováno:
2010, Proceedings of the 18th Annual Conference Technical Computing Bratislava, Bratislava, Systémy priemyselnej informatiky s.r.o.), p. 1-9), ISBN 978-80-970519-0-7
Anotace:
The paper concerns the Bayesian modelling of tra c intensities measured in towns and cities. It proposes the use of a normal regressive model of low order, whose parameters (regression coe cients) are estimated using partial forgetting. This method allows to track the time varying parameters and respects the dierent variability rate of the absolute term modelling the mean value. The general theoretical concept of Bayesian modelling and parameter estimation is complemented with the theory related to the normal model in lieu.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Ing. Jan Krčál, Ph.D.; doc. Ing. Ivan Nagy, CSc.; Ing. Mgr. Michal Jeřábek, Ph.D.
Publikováno:
2009, Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship, New York, ACM), p. 198-201), ISBN 978-1-60558-398-3
Anotace:
In the light of today´s high traffic volume, it is crucial to anticipate the traffic flow on traffic lights controlled intersections. Without this knowledge, it would be impossible to control the traffic in complicated hubs, such as, for instance, those in Prague. One of the characteristics, through which we can describe dynamics of vehicle movement on traffic lights controlled intersections, is the interval between departure of a vehicle from the space in front of the stop line and the arrival to the actual stop line. This is called a departure model. Our aim is, first, to create an appropriate mathematical application, which would take into account individual variables influencing departure of individual vehicles and determine the dependence among these variables. Second to create such a departure model, which would, on one hand, correspond as much as possible to the contemporary traffic situations, but on the other hand, be more exact for specific intersections.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.; Homolová, J.; Ing. Pavla Pecherková, Ph.D.
Publikováno:
2007, Automa, 6 (13), p. 12-16), ISSN 1210-9592
Anotace:
Článek ze zabývá modelováním dopravní oblasti, odhadem tohoto modelu a optimálním řízením, založeném na odvozeném modelu a lineárním kriteriu optimality. Řízení je hierarchické - optimalizace kolon v mikrooblasti a koordinace mezi nimi.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
doc. Ing. Ivan Nagy, CSc.; Homolová, J.; Ing. Pavla Pecherková, Ph.D.
Publikováno:
2007, Automa, 7 (13), p. 61-64), ISSN 1210-9592
Anotace:
Dopravní mikrooblast je popsána stavovým modelem. Modelovanou veličinou jsou délky kolon a ty jsou odhadovány pomocí Kalmanova filtru, nebo některou jeho nelineární verzí (DD1 atd.) Řízení, založené na lineárním programování, minimalizuje vážený součet délek kolon. Činnost lokálního řízení je koordinována pomocí nadřazeného řízení.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
doc. Ing. Ivan Nagy, CSc.; Gebouský, P.; Homolová, J.
Publikováno:
2006
Anotace:
Práce je pokusem o obecné teoretické řešení problematiky odhalování výjimečných stavů v dopravě (t.j. havárií, nadměrné zátěže způsobené výjimečnou koncentraci vozidel, práce na vozovce apod.) a přibližným určením, kde k tomuto stavu došlo. Teorie je založena na popisu sledované oblasti modelem směsi distribucí a analýzou této směsi pomocí likelihoodu variant.
Typ:
Oponovaná výzkumná zpráva v češtině

Autoři:
Ing. Pavla Pecherková, Ph.D.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2006, Acta Polytechnica, 46 (2), p. 30-35), ISSN 1210-2709
Anotace:
The data are modelled by a mixture with two components. The first component models the pure data, the second one the outliers. If the weights of the components, which are currently estimated, show that the actual data is outlier, the data is substitutes by a prediction from the data component.
Typ:
Článek v odborném recenzovaném periodiku cizojazyčně

Autoři:
doc. Ing. Ivan Nagy, CSc.; Homolová, J.; doc. Ing. Evženie Uglickich, CSc.
Publikováno:
2006, FOSLET 2006, Lugano, Impressum), p. 13-20)
Anotace:
The paper deals with a teaching system for Bayesian Statistics. The system aims at PhD students, who are provided with a theory of Bayesian modelling, estimation and prediction of dynamic systems under uncertainty. The theory is supplied by programs in the system MATLAB, where the theoretical results can be verified as well as new programs can be constructed.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Homolová, J.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2006, Pedagogický software 2006, České Budějovice, Scientific Pedagogical Publishing), p. 1-3), ISBN 80-85645-56-4
Anotace:
V příspěvku byl prezentován výukový systém pro výuku statistiky. Systém je tvořen dvěma částmi: první je interaktivní text s prezentací teorie, druhá obsahuje popisy příkladů a jejich algoritmické řešení naprogramované v systému Octave. Celý systém je otevřený a lze jej libovolně rozšiřovat
Typ:
Stať ve sborníku z lokální konf. česky

Autoři:
doc. Ing. Tomáš Tichý, Ph.D., MBA; doc. Ing. Ivan Nagy, CSc.; Homolová, J.
Publikováno:
2005, Sborník ITS 05 Praha, Praha, Wirelesscom), p. 33-34), ISBN 80-239-4447-9
Anotace:
Příspěvek se zabývá návrhem a implementací systému optimálního řízení dopravy v městských oblastech. Cílem je shrnout problémy a případná úskalí při optimalizaci dopravních toků v síti s přihlédnutím k preferenci městské hromadné dopravy, přímému informování řidičů a návaznosti na bezpečnostní systémy městských tunelů. Jednou z cest k řešení tohoto problému je vypracování koncepce telematického systému města, jejímž cílem bude zlepšit propustnost dopravní sítě s přihlédnutím ke všem požadavkům na moderní trendy rozvoje dopravy ve městech a regionech.
Typ:
Stať ve sborníku z lokální konf. česky

Autoři:
Kárný, M.; Bohm, J.; Guy, T.V.; Jirsa, L.; doc. Ing. Ivan Nagy, CSc.; Nedoma, P.; Tesař, L.
Publikováno:
2005, ISBN 1-85233-928-4
Anotace:
This work summarizes the theoretical and algoritmic basis of optimized probabilistic advising. It developed from a series of targeted research projects supported by EC & Czech grant bodies. The source text has served as a common basis of communication for the research team. The final text may serve as - a grand example of dynamic Bayesian decision making - a reference to ready particular solutions in learning and optimization of decision-making strategies - a source of open challenging research problems.
Typ:
Vědecká kniha

Autoři:
Kárný, M.; Kracík, J.; doc. Ing. Ivan Nagy, CSc.; Nedoma, P.
Publikováno:
2005, International Journal of Adaptive Control and Signal Processing, 19 (1), p. 41-57), ISSN 0890-6327
Anotace:
The paper deals with Bayesian estimation of dynamical regression models or their mixtures. The main contribution of the paper is presentation of a test for finishing the data acquisition and running estimation for the case that the estimation is sufficient. The test is recommended especially in the cases when the data used are expensive.
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
Homolová, J.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2004, CMP'04: Multiple Participant Decision Making, Theory, Adelaide, Advanced Knowledge International), p. 161-171), ISBN 0-9751004-5-9
Anotace:
The paper deals with urban transportation control problem. A traffic micro-region is modelled by a linear state-space model, describing output intensity of traffic flow in dependence on intensities and occupances of input traffic flow. As a state of the model stay column lengths in crossroads and unmeasurable input intensities. The control represents first level of a hierarchical controller, which is supposed to be constructed in the future.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Homolová, J.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2004, Automatizace, 47 (12), p. 752-758), ISSN 0005-125X
Anotace:
Článek uvádí novou koncepci stavového modelu dopravní mikrooblasti. Model je využit pro odhadování délek kolon, které se tvoří v ramenech křižovatek na světelné signalizaci. Tato úloha je jednoduchá, jestliže všechny potřebné veličiny jsou měřeny. Model pak jednoduše počítá délky kolon ze vstupních a výstupních intenzit dopravního proudu. Často však některé potřebné veličiny nejsou měřitelné. V tomto případě dochází k odhadu délek kolon. V závěru článku jsou uvedeny výsledky simulačních experimentů.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
Kárný, M.; Nedoma, P.; Guy, T.; Knížek, J.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2003, Automatizace, 46 (3), p. 177-179), ISSN 0005-125X
Anotace:
Článek se zabývá problematikou operátorského řízení pro složité systémy. je založen na modelu směsi distribucí. Tento model je odhadován z dat, měřených na uzavřené smyčce systém-operátor. Jednotlivé stavy systému a zásahů operátora. Po odhadu modelu a vyhodnocení jeho komponent podle uživatelského kritéria lze model využít pro navádení operátora na nejlepší stav systému v závislosti na průběžně měřených datech.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
doc. Ing. Ivan Nagy, CSc.; Kárný, M.; Nedoma, P.; Mgr. Šárka Voráčová, Ph.D.
Publikováno:
2003, International Journal of Adaptive Control and Signal Processing, 17 (1), p. 51-65), ISSN 0890-6327
Anotace:
The paper deals with modelling and estimation by a model described as a mixture of distriburions. In this case, the exact application of the Bayes theory adopted is not feasible and its approximation is used. The general algorithm is specified for mixtures with components from ixponential family. The theory is demonstrated on estimation of the basic relation between density and intensity of traffic flow in a single point of a vehicular communication and it can provide us with state closiification.
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
doc. Ing. Ivan Nagy, CSc.; Kratochvílová, J.; Němcová, P.
Publikováno:
2003, Doprava a telekomunikace pro 3. tisíciletí, Praha, České vysoké učení technické v Praze, Fakulta dopravní), p. 205-210), ISBN 80-01-02741-4
Anotace:
The basic notions and principles of the application of Bayesian approach to modelling, estimation and control in transportation area are mentioned. The theoretical outline is supplied by results of a practical application-prediction of characteristic of traffic flow in a single point of prague communication.
Typ:
Stať ve sborníku z fakultní konference cizojazyčně

Autoři:
Kratochvílová, J.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2003
Anotace:
Over view of optimisation methods of signal traffic control developed during the last 10 years.
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
doc. Ing. Ivan Nagy, CSc.
Publikováno:
2003
Typ:
Docentská habilitační práce

Autoři:
Quin, A.; Ettler, P.; Jirsa, L.; doc. Ing. Ivan Nagy, CSc.; Nedoma, P.
Publikováno:
2003, International Journal of Adaptive Control and Signal Processing, 17 (2), p. 133-148), ISSN 0890-6327
Anotace:
The paper deals with mixture modelling as a tool for estimation and control of real-world, multidimensional, dynamic, non-linear processes. The experience gained under the EU project ProDaCTool, in designing and implementing advisory systems in urban traffic regulation, theraty recommendations in nuclear medicine and operator support for metal-striprolling mill are presented.
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
Pavelková, L.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
2003
Anotace:
Search for an Optimal Setup of Stabilized Forgetting in Estimation
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
doc. Ing. Ivan Nagy, CSc.
Publikováno:
2003, ISBN 80-01-02748-1
Anotace:
Monografie podává základy bayesovského přístupu k modelování, identifikaci a řízení stochastických soustav, se zaměřením na dopravní systémy. První část práce je věnována motivaci studované problematiky a demonstraci zákldních pojmů z oblasti modelování dynamických systémů. Jsou rovněž uvedeny základní pojmy teorie pravděpodobnosti, formulované z hlediska bayesovské statistiky. hlavní část práce je věnována modelování, identifikaci a řízení.
Typ:
Jiná kniha česky

Autoři:
doc. Ing. Ivan Nagy, CSc.
Publikováno:
2002
Anotace:
The qasi-Bayes algorithm, developed in the framework of EU grant Prodactool, is used for mixture estimation. This report provides systematic testing of the abilities of the algorithm for estimation of static mixtures. For testing,known and described types of difficult data samples are used.The results of quasi-Bayes alforithm are evaluated by comparison of data clusters and clusters of data, obtained by simulation form the estimated mixture.
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
doc. Ing. Ivan Nagy, CSc.
Publikováno:
2002
Anotace:
The qasi-Bayes algorithm, developed in the framework of EU grant Prodactool, is used for mixture estimation. This report provides systematic testing of the abilities of the algorithm for estimation of dynamic mixtures. For testing, real data samples are used. They are data from rolling mill in Rokycany and transportation data from Strahov tunel. The results of quasi-Bayes algorithm are evaluated by comparison of data clusters and predicted clusters, by value of log-likelihood of variants and by evaluating prediction error for time domain prediction.
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
Kárný, M.; doc. Ing. Ivan Nagy, CSc.; Novovičová, J.
Publikováno:
2002, International Journal of Adaptive Control and Signal Processing, 16 (1), p. 61-83), ISSN 0890-6327
Anotace:
Early recognition/isolation of a faulty behaviour of a dynamic system is the main task of a fault detection and isolation (FDI). FDI methods based on adaptive probabilistic models with multiple modes represent a theoretically well justified way of solution. Their use is severely restricted by an inherent computational complexity. The complexity problem is addressed here by employing an efficient quasi-Bayes estimation algorithm. It is directly applicable to the mixture of components created as products of factors belonging to the exponential family. It opens a novel way to deal adaptively with mixed continuous-discrete, dynamically related data. The presented theory and algorithmization are illustrated by a simple simulation example.
DOI:
10.1002/acs.672
Typ:
Článek v periodiku excerpovaném SCI Expanded

Autoři:
Nedoma, P.; Bohm, J.; Guy, T.; Jirsa, L.; Kárný, M.; doc. Ing. Ivan Nagy, CSc.; Tesař, L.; Andrýsek, J.
Publikováno:
2002
Anotace:
The program package Mixtools is the main software tool for simulation, estimation, prediction and control with mixture models as a descriptors of the investigated system. This report gives a guide for using the toolbox. It is equipped with many examples enlightening the software usage.
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
doc. Ing. Ivan Nagy, CSc.; Nedoma, P.; Kárný, M.; Pavelková, L.; Ettler, P.
Publikováno:
2002, Automa, 8 (12), p. 44-49), ISSN 1210-9592
Anotace:
Tento článek bezprostředně navazuje na stejnojmenný článek, uveřejněný v předchozím čísle časopisu. Popsanou teorii doplňuje experimenty s identifikací modelů směsi distribucí. Pro testování jsou použita mnohorozměrná drálná data z válcovací stolice pro výrobu plechových pásů a z dopravní oblasti. Pro vyhodnovení úspěšnosti odhadu modelu je sledována zejména jeho schopnost predikce.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
doc. Ing. Ivan Nagy, CSc.; Nedoma, P.; Kárný, M.; Pavelková, L.; Ettler, P.
Publikováno:
2002, Automa, 8 (11), p. 54-57), ISSN 1210-9592
Anotace:
Článek podává základní informaci o popisu složitých systémů pomocí modelu směsi distribucí a identifikaci takového modelu s využitím bayesovského přístupu. Uvažovaný model je schopen popsat systémy s několika stavy, jejichž souvislosti mohou být obecně nelineární. Metoda identifikace provádí shlukovou analýzu a výsledný model je nejen dobrým statistickým popisem reality, ale zároveň poskytuje i průběžnou klasifikaci stavu systému. Uvedená teorie modelování a identifikace lze využit pro konstrukci poradního systému pro operátory složitých procesů. Tato první část článku se zabývá popisem teorie.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
doc. Ing. Ivan Nagy, CSc.; Nedoma, P.; Kárný, M.; Pavelková, L.; Ettler, P.
Publikováno:
2002, Automa, 8 (7), p. 56-60), ISSN 1210-9592
Anotace:
Článek prezentuje základní principy bayesovského odadování náhodných procesů. Výklad je průběžně ilustrován jejjednodušším možným příkladem-hodem porušenou mincí a odhadování pravděpodobnosti padnutí lícu.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
doc. Ing. Ivan Nagy, CSc.
Publikováno:
2002, ISBN 80-01-02454-7
Anotace:
Skriptum je základní sbírkou úloh pro předmět Pravděpodobnost a matematická statistika na FD ČVUT. Vedle sbírky příkladů jsou zde uvedeny i teoretické souhrny jednotlivých celků a typové úlohy s jejich podrobným řešením.
Typ:
Vysokoškolské skriptum v češtině

Autoři:
doc. Ing. Ivan Nagy, CSc.
Publikováno:
2002
Anotace:
Zpráva navazuje na dvě předchozí práce, které pojednávaly o základech bayesovského odhadování a řízení v dopravní problematice. Tato zpráva doplňuje některé speciální modely, které jsou zvláště výhodné pro popis dopravních systémů. Jedná se o modely směsí, které popisují obecně dynamické systémy s více stavy, mezi nimiž se systém přepíná. Dále jsou to modely (nebo jejich směsi) s aproximací pomocí spline-funkce, které se hodí pro popis hladkých signálů.
Typ:
Výzkumná zpráva v češtině

Autoři:
Kárný, M.; doc. Ing. Ivan Nagy, CSc.; Nedoma, P.; Guy, T.; Knížek, J.; Ettler, P.
Publikováno:
2002, Chemagazín, 12 (4), p. 14-16), ISSN 1210-7409
Anotace:
Článek prezentuje základy modelování pomoci směsi distribucí pro dynamické systémy, které lze využít pro shlukovou analýzu. Modelování a odhad směřuje k využití jako systém pro podporu operátorů složitýcz systémů.
Typ:
Článek v odborném recenzovaném periodiku česky

Autoři:
Knížek, J.; doc. Ing. Ivan Nagy, CSc.; Nedoma, P.; Kárný, M.
Publikováno:
2002
Anotace:
The report deal with initialization of the algorithm of Bayesian estimation of mixture models. It suggests an initialization composed of two basic algorithms: the MT (mean tracking) and quasi Bayes algirithm. It tests results estimation with this combination, called BMTB algorithm and without it and shows that the improvement is statistically significant.
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
doc. Ing. Ivan Nagy, CSc.; Kárný, M.; Nedoma, P.
Publikováno:
2001, Artificial Neural Nets and Genetic Algorithms, Wien, Springer), p. 402-405), ISBN 3-211-83651-9
Anotace:
A classical version of the EM (expectation and Maximization) algorithm is considered in the paper. Its numerical properties are improved using factorized algorithms for maximization in M step of the algorithm. The results are illustrated on simulated examples.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
Kárný, M.; Nedoma, P.; doc. Ing. Ivan Nagy, CSc.; Válečková, M.
Publikováno:
2001, Artificial Neural Nets and Genetic Algorithms, Wien, Springer), p. 398-401), ISBN 3-211-83651-9
Anotace:
Complexity of real systems imply that resulting description depends heavily on its intialization.The paper describes a novel technique of dynamical model initialization when the trial description is gradually split whenever there is possibility that a unimodal sub-model hides more modes.
Typ:
Stať ve sborníku z mezinár. konf.

Autoři:
doc. Ing. Ivan Nagy, CSc.
Publikováno:
2001
Anotace:
Práce se zabývá problematikou bayesovského modelování dynamických systémů, jejich identifikací a optimálním řízením. Identifikace je založena na přepočtu apriorní hustoty pravděpodobnosti na aposteriorní, syntéza řízení je vychází ze stochastické verze dynamického programování.
Typ:
Výzkumná zpráva v češtině

Autoři:
Nedoma, P.; Kárný, M.; doc. Ing. Ivan Nagy, CSc.; Valečková, M.
Publikováno:
2000
Anotace:
Mixtools-MATLAB Toolbox for Mixtures Mixtools-MATLAB Toolbox for Mixtures Mixtools-MATLAB Toolbox for Mixtures Mixtools-MATLAB Toolbox for Mixtures Mixtools-MATLAB Toolbox for Mixtures Mixtools-MATLAB Toolbox for Mixtures
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
doc. Ing. Ivan Nagy, CSc.
Publikováno:
2000
Anotace:
Rozhodování a řízení v dopravě, Rozhodování a řízení v dopravě, Rozhodování a řízení v dopravě, Rozhodování a řízení v dopravě, Rozhodování a řízení v dopravě, Rozhodování a řízení v dopravě, Rozhodování a řízení v dopravě,
Typ:
Výzkumná zpráva v češtině

Autoři:
Kárný, M.; Nedoma, P.; doc. Ing. Ivan Nagy, CSc.; Valečková, M.
Publikováno:
2000
Anotace:
Mixture estimation Mixture estimation Mixture estimation Mixture estimation Mixture estimation Mixture estimation Mixture estimation Mixture estimation Mixture estimation Mixture estimation
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
Kárný, M.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
1999
Anotace:
Dynamic decision making. Dynamic decision making. Dynamic decision making. Dynamic decision making. Dynamic decision making. Dynamic decision making. Dynamic decision making.
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
doc. Ing. Ivan Nagy, CSc.; Kárný, M.; Novovičová, J.; Valečková, M.
Publikováno:
1999
Anotace:
Mixture-Model Identification in Traffic Control Problems Mixture-Model Identification in Traffic Control Problems Mixture-Model Identification in Traffic Control Problems
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
Prchal, J.; Kárný, M.; prof. Dr. Ing. Miroslav Svítek, dr. h. c.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
1999, Transfer'99, Brno, VUT v Brně), p. 15-16), ISBN 80-214-1341-7
Anotace:
Článek s zabývá problematikou dopravního řízení. Speciální důraz se klade na inicializaci řídících algoritmů tak, aby jejich nasazování vyžadovalo co nejmenší počet parametrů, které je třeba ručně nastavit.
Typ:
Stať ve sborníku z lokální konf. česky

Autoři:
Kárný, M.; doc. Ing. Ivan Nagy, CSc.; Novovičová, J.
Publikováno:
1999
Anotace:
Fault detection Fault detection Fault detection Fault detection Fault detection Fault detection Fault detection Fault detection Fault detection Fault detection Fault detection
Typ:
Výzkumná zpráva cizojazyčně

Autoři:
Prchal, J.; prof. Dr. Ing. Miroslav Svítek, dr. h. c.; Kárný, M.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
1999, Proceedings of Workshop 99, Praha, České vysoké učení technické v Praze), p. 426-426)
Anotace:
Traffic systems modeling based on the reduced data vector Traffic systems modeling based on the reduced data vector Traffic systems modeling based on the reduced data vector Traffic systems modeling based on the reduced data vector
Typ:
Stať ve sborníku Workshop ČVUT

Autoři:
Halousková, A.; Kárný, M.; doc. Ing. Ivan Nagy, CSc.
Publikováno:
1993, Automatica, 29 (2), p. 425-429), ISSN 0005-1098
Anotace:
Adaptive cross direction control of paper basis weight was solved, using a model based on the approximation of smooth kernels of integral operators by spline function of a proper order
Typ:
Článek v odborném recenzovaném periodiku

Autoři:
Kárný, M.; doc. Ing. Ivan Nagy, CSc.; Bohm, J.; Halousková, A.
Publikováno:
1990, Kybernetika, 26 (1), p. 17-30), ISSN 0023-5954
Anotace:
Spline-based self-tuners were designed Spline-based self-tuners were designed and tested in some examples. The paper describes it and discussed also other topics.
Typ:
Článek v periodiku excerpovaném SCI Expanded