Systems modeling
Course: Software Engineering
Structural unit: Faculty of Computer Science and Cybernetics
Title
Systems modeling
Code
ННД.29
Module type
Обов’язкова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2021/2022
Semester/trimester when the component is delivered
5 Semester
Number of ECTS credits allocated
3
Learning outcomes
PLO 1 Know, analyze, purposefully search for and select the necessary information and reference resources and knowledge to solve professional problems, taking into account modern advances in science and technology.
Form of study
Full-time form
Prerequisites and co-requisites
To successfully study the discipline " Systems modeling" the student must meet the following requirements:
1. Know:
1) standard courses in mathematical analysis, linear algebra, discrete mathematics, differential equations, operations research, numerical methods;
2) software for modeling systems.
2. Be able to:
1) Apply basic algorithms for filtering, restoration, recognition in information processing.
2) Apply algorithms for digital information processing.
3. Possess:
1) solve systems of linear algebraic equations with parameters, solve differential equations, study functions and functionals to the extreme, have the skills to build, analyze and apply mathematical models in solving applied problems.
Course content
The purpose of the discipline is to get acquainted with and acquire theoretical and practical knowledge in the field of systems modeling. Methods, algorithms, and examples of construction and analysis of mathematical models for some problems of mechanics, biology are offered. During training, students will get acquainted with the basic algorithms of the identification of parameters of dynamic systems.
Recommended or required reading and other learning resources/tools
1. Molchanov AA Modeling and design of complex systems. - K .: Higher school, 1988.
2. Zarubin VS Mathematical modeling in engineering. - М .: MGTU of N E Bauman, 2001.
3. Matvienko V.T. Optimal of multidimensional modal control. Journal of Advanced Research in Technical Science. 2019. – Issue 15. – p. 110-116. – North Charleston, USA.
Planned learning activities and teaching methods
Lectures, laboratory work, independent work, elaboration of recommended literature, homework.
Assessment methods and criteria
Semester assessment:
A maximum number of points that can be obtained by a student: 100 points:
1. Test work №1: - 25/15 points.
2. Test work № 2: - 25/15 points.
3. Oral answers: - 10/6 points.
4. Testing of students' knowledge: - 30/18 points.
5. Summary: - 10/6 points.
Final assessment (in the form of a test):
- Credit points are defined as the sum of grades/points for all successfully assessed learning outcomes provided by this program.
- Scores below the minimum threshold are not added.
- The minimum threshold for the total assessment of all components is 60% of the maximum possible number of points.
Language of instruction
Ukrainian
Lecturers
This discipline is taught by the following teachers
Volodymyr
T.
Matvienko
Complex systems modelling
Faculty of Computer Science and Cybernetics
Faculty of Computer Science and Cybernetics
Yaroslav
Pavlovych
Trotsenko
Complex systems modelling
Faculty of Computer Science and Cybernetics
Faculty of Computer Science and Cybernetics
Departments
The following departments are involved in teaching the above discipline
Complex systems modelling
Faculty of Computer Science and Cybernetics
Complex systems modelling
Faculty of Computer Science and Cybernetics