Methods of mathematical modeling
Course: Applied Mathematics
Structural unit: Faculty of Computer Science and Cybernetics
            Title
        
        
            Methods of mathematical modeling
        
    
            Code
        
        
            ДВС.2.04 
        
    
            Module type 
        
        
            Вибіркова дисципліна для ОП
        
    
            Educational cycle
        
        
            First
        
    
            Year of study when the component is delivered
        
        
            2022/2023
        
    
            Semester/trimester when the component is delivered
        
        
            7 Semester
        
    
            Number of ECTS credits allocated
        
        
            3
        
    
            Learning outcomes
        
        
            LO01. Demonstrate knowledge and understanding of basic concepts, principles, and theories of fundamental and applied mathematics and use them in practice.
LO11. Be able to apply modern technologies of programming and software development, software implementation of numerical and symbolic algorithms.
LO15. Be able to organize their activities and get results within a limited time.
PLO23.2. Be able to analyze independently the subject area and develop mathematical and structural-algorithmic models.
        
    
            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, and have methods of numerical differentiation and integration.
2. Possess skills in 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 constructing mathematical models of spatially distributed dynamic processes and phenomena, as well as mathematical modeling of their state in the conditions of the incompleteness of information about their external-dynamic state and methods of managing it.
        
    
            Recommended or required reading and other learning resources/tools
        
        
            1. Stoyan V.A. Matematychne modeliuvannia liniinykh, kvaziliniinykh i neliniinykh dynamichnykh system. – K.: VPTі "Kyivskyi Universytet", 2011. – 320 p.
2.  Stoyan V.A. Modeliuvannia ta identifikatsiya dynamiky system z rozpodilenymy parametramy. – K.: VPTі "Kyivskyi Universytet", 2004. – 184 p.
3.  Stoyan V.A. Osnovy laboratornoho modeliuvannia prostorovo rozpodilenykh dynamichnykh system. – K.: VPTі "Kyivskyi Universytet", 2017. – 118 p.
        
    
            Planned learning activities and teaching methods
        
        
            Lectures, laboratory works, independent work.
        
    
            Assessment methods and criteria
        
        
            Semester assessment:
The maximum number of points that can be obtained by a student is 60 points:
1. Practical work - 12/7 points.
2. Current assessment - 12/7 points.
3. Oral answers - 12/7 points.
4. Practical work - 12/7 points.
5. Oral answers - 12/8 points.
Final assessment in the form of an exam:
- the maximum number of points that can be obtained by a student is 40 points;
- a form of conducting: written work.
Types of tasks: 3 written tasks (2 theoretical questions of 10 points and 1 practical
task - 20 points).
        
    
            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
            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