Technologies of mathematical and computer modeling

Course: Applied Mathematics

Structural unit: Faculty of Computer Science and Cybernetics

Title
Technologies of mathematical and computer modeling
Code
ДВС.2.07
Module type
Вибіркова дисципліна для ОП
Educational cycle
First
Year of study when the component is delivered
2021/2022
Semester/trimester when the component is delivered
8 Semester
Number of ECTS credits allocated
6
Learning outcomes
PLO1. Demonstrate knowledge and understanding of basic concepts, principles, and theories of fundamental and applied mathematics and use them in practice. PLO5. Be able to develop and use in practice algorithms related to the approximation of functional dependencies, numerical differentiation and integration, solving systems of algebraic, differential and integral equations, solving boundary value problems, finding optimal solutions. PLO9. Combine methods of mathematical and computer modeling with informal expert analysis procedures to find optimal solutions. PLO13. Solve particular engineering problems and/or problems that arise in at least one subject area: sociology, economics, ecology, and medicine. PLO20. PLO22.2. PLO24.2. PLO26.2 http://csc.knu.ua/media/filer_public/6a/29/6a29dc9d-47c9-46ef-aacd-67e1d899140e/opp_pm_2018__1.pdf
Form of study
Full-time form
Prerequisites and co-requisites
1. Be able to: formulate and solve initial-boundary value problems of mathematical physics, solve systems of linear algebraic equations, master methods of numerical differentiation and integration. 2. Master: skills of practical construction and software implementation of algorithms and methods of classical computational mathematics in solving applied problems.
Course content
The purpose of the discipline: mastering the principles of building mathematical models of spatially distributed dynamic processes and phenomena, as well as dynamic models with aftereffect and mathematical modeling of their state in conditions of incomplete information about their external dynamic state, and developing methods for managing these processes.
Recommended or required reading and other learning resources/tools
1. Stoyan V.A. Matematychne modeliuvannia liniinykh, kvaziliniinykh i neliniinykh dynamichnykh system. – K.: VPTS "Kyivskyi Universytet", 2011. – 320 s. 2. Stoyan V.A. Modeliuvannia ta identyfikatsiia dynamiky system z rozpodilenymy parametramy. – K.: VPTS "Kyivskyi Universytet", 2004. – 184 s. 3. Stoyan V.A. Osnovy laboratornoho modeliuvannia prostorovo rozpodilenykh dynamichnykh system. – K.: VPTS "Kyivskyi Universytet", 2021. – 174 s.
Planned learning activities and teaching methods
Lectures, laboratory works, independent work.
Assessment methods and criteria
Semester assessment: A maximum number of points that can be obtained by a student: 60 points: 1. Test work № 1 - 20/12 points. 2. Current evaluation - 20/12 points. 2. Test work № 2 - 20/12 points. Final assessment in the form of an exam: The maximum number of points that can be obtained by a student is 40 points. - Form of conducting: written work. - Types of tasks for each module: 1 theoretical question.
Language of instruction
Ukrainian

Lecturers

This discipline is taught by the following teachers

Volodymyr A. Stoyan
Complex systems modelling
Faculty of Computer Science and Cybernetics
Denys Yakhievych Khusainov
Complex systems modelling
Faculty of Computer Science and Cybernetics