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19M081MMS - Mathematical modeling and simulations

Course specification
Course title Mathematical modeling and simulations
Acronym 19M081MMS
Study programme Electrical Engineering and Computing
Module
Type of study master academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
    ESPB 6.0 Status elective
    Condition Mathematical subjects of bachelor studies
    The goal Linking and applying knowledge in Mathematics, Electrical Eengineering and Computer Science in forming mathematical models describing real systems in different fields, and creating simulations - computer experiments, based on formed models, that are necessary to understand, anticipate, and optimize modeled systems.
    The outcome Upon completion of the course, the student is able to define, describe and apply basic concepts related to mathematical modeling and simulation of many contemporary problems in the field of Electrical Engineering and Computer Science, and to solve the selected problems by applying adequate mathematical methods and computer tools by creating simulations.
    Contents
    Contents of lectures Introduction to mathematical modeling and simulation, simulation cycle; Model classes, selection of tools for describing models, performance model properties. Examples of discrete models and simulation methods (game theory, decision theory, discrete events). Examples of continuous models and simulations (dynamic systems, traffic simulations, models based on partial differential equations).
    Contents of exercises Through examples, tasks and problems, a student learns how to apply theorems and basic concepts studied though theoretical concepts. Student is specially prepared to solve problems that arise in Electrical Engineering subjects, using mathematical software packages.
    Literature
    1. Hans-Joachim Bungartz e.a.: Modeling and Simulation: An Application-Oriented Introduction, Springer, 2013
    2. Milan Drazic, Mathematical modeling, Mathmatical Faculty, Belgrade, 2017, in serbian
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    3 1
    Methods of teaching Combination of traditional presentation on blackboard, use of slides, free mathematical software (SAGE, Python with libraries), individual work with students on the projects and explanation of current topics.
    Knowledge score (maximum points 100)
    Pre obligations Points Final exam Points
    Activites during lectures Test paper 20
    Practical lessons Oral examination 20
    Projects 60
    Colloquia
    Seminars