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Stochastic Systems

Course Code:
11STS
Academic Degree:
master
Study Programme:
Transportation Systems and Technology (N1041A040003)
semesterlanguage
3czech flag
Logistics and Transport Processes Control (N1041A040005)
semesterlanguage
3czech flag
Erasmus:
course for Erasmus and Exchange students in winter semester
Form of Study:
full-time and part-time
Credits:
4
Number of Hours:
2 + 2 hours per week - in full-time study
14 hours per semester - in part-time study
Type of Course:
obligatory
Course Completion:
credit, exam
Supervisor:
doc. Ing. Evženie UGLICKICH, CSc.
Course Tutor:
 
roh  Lectures:
doc. Ing. Evženie Uglickich, CSc.
roh  Training Course:
Ing. Raissa Likhonina, Ph.D.
Ing. Michal Matowicki, Ph.D.
doc. Ing. Evženie Uglickich, CSc.
roh  Part-time Study:
Ing. Pavla Pecherková, Ph.D.
Supervising Department:
Department of Applied Mathematics (16111)
Keywords:
Stochastic processes, dynamic system model, estimation of parameters of a linear regression model, estimation of parameters of a discrete model, prediction with dynamic model, modelling of transportation systems.
Abstract:
The subject deals with the problems of mathematical modelling of dynamical systems, estimation od these models and their utilization for prediction. The results are illustrated on practical transportation tasks. Mathematical theory roots from probability and mathematical statistics and they use the methods of the Bayesian probabilistic approach.
Objectives:
The goal will be the description of stochastic processes, their estimation and their use for prediction, classification and control. The theory will be illustrated in transportation problems.