System Simulation | Centre for Joint Academic Programmes

Level: Bachelor

Semestre: 1st

ECTS: 4

Working Hours:

- Contact: 26

- Self-study: 118

- Total: 144

Language of Instruction: English

Author of the Course: Professor Stanislav V. Shidlovskiy

Lecturers:

Professor Stanislav V. Shidlovskiy

Objectives:

- to develop knowledge and skills of applying the general methods in system modeling, types of mathematical models, mathematic simulation methods on the base of continuously determinate, discrete determinate, probabilistic, aggregative models, to develop understanding of goal setting and simulation method selection, validity check of mathematical model to real complex system, understanding of simulation results.

Learning Outcomes:

to know:

- information collection and processing methods, separate aspects which characterize the problem;

- basics of mathematic simulation theory;

- basic stages in organization of research work, basic requirements to execution and content of records on research work performed, formulae, tables etc. submission guidelines;

- dynamic optimization models; mathematic models of optimal control for continuous and discrete processes, their comparative study;

- basic analytical models and numerical methods of mathematic simulation;

- software tools of mathematic simulation;

be able to:

- use listed knowledge in exploratory and experimental activity which requires to use mathematic simulation methods;

- set the goals of simulation, find out links between figures, use the in model received information for process management;

- represent problems and define objects and tasks of research;

- conduct problem analysis with mathematic simulation methods on the base of basic mathe

matic knowledge;

be master of:

- scientific knowledge method;

- skills of information models creation;

- analytical and quantitative methods in solving of standard mathematic models;

- methods of optimal control of continuous and discrete processes for optimization of application and information processes;

- techniques of computing mathematic simulation;

- skills of analytical and numerical mathematic simulation.