Infopaket

Mathematical modeling

Вибіркова дисципліна для ОП

First

2021/2022

6 Semester

3

PLO2. Use modern mathematical apparatus of continuous and discrete analysis, linear algebra, and analytical geometry to solve theoretical and applied problems in the design and implementation of informatization objects. PLO3. Demonstrate knowledge of the laws of random phenomena, their properties and operations on them, models of random processes, and modern software environments for solving problems of statistical processing of experimental data and construction of predictive models. PLO4. Design, develop and analyze algorithms for solving computational and logical problems, evaluate the efficiency and complexity of algorithms based on the use of formal models of algorithms and computational functions. PLO7. Be able to apply the methodology of simulation modeling of objects, processes, and systems, plan and conduct experiments with models, make decisions about achieving the goal based on the results of modeling.

Full-time form

To successfully study the discipline "Mathematical modeling" the student must meet the following requirements: 1. Successful mastering of courses: 1) Mathematical analysis. 2) Linear algebra. 3) Differential equations. 4) Programming. 2. Knowledge of: 1) Theoretical bases and methods of construction, verification, and research of qualitative characteristics of systems. 2) Principles of building stationary and dynamic models. 3. Skills: 1) Solve systems of linear algebraic equations. 2) Solve differential equations and systems of differential equations. 3) Analyze the modeled systems. 4. Possession of: 1) Basic skills in programming and using application packages for numerical analysis (WOLFRAM MATHEMATICA, Python). 2) Skills at the application of mathematical apparatus in the construction and analysis of mathematical models.

The purpose of the discipline is to master theoretical and practical knowledge in the field of mathematical modeling. Mastering the methods and algorithms of construction and analysis of mathematical models of various processes.

1. Matsenko, V.H. (2014). Matematychne modeliuvannia: navchalnyi posibnyk. Chernivtsi: Chernivetskyi natsionalnyi universytet. 2. Stanzhytskyi, O.M., Taran, Ye.Iu., & Hordynskyi, L.D. (2006). Osnovy matematychnoho modeliuvannia: navchalnyi posibnyk. K., VPTs “Kyivskyi universytet”. 3. Stoyan, V.A. (2019). Matematicheskoe modelirovanie dinamiki nepolno nablyudaemykh lineynykh prostranstvenno raspredelennykh sistem: Monografiya. K., VPTs “Kievskiy universitet”. 4. Korobeynikov, V.P. (1996). Printsipy matematicheskogo modelirovaniya. Vladivostok, Dalnauka. 5. Samarskiy, A.A., & Mikhaylov A.P. (1997). Matematicheskoe modelirovanie. M., Nauka.

Lectures, off-class work, the study of recommended literature.

Semester evaluation: The maximum score that can be received by a student: 100 points: 1. Lab work №1: - 20/12 points. 2. Lab work №2: - 20/12 points. 3. Lab work №3: - 20/12 points. 4. Lab work №4: - 20/12 points. 5. Test №1: - 20/12 points. Final assessment (credit): According to paragraphs. 4.6.1 and 7.1.5 "Regulations on the organization of the educational process at the Taras Shevchenko National University of Kyiv " credit is based on the current control (see semester assessment) as the sum of grades/scores on all successfully evaluated learning outcomes; scores below the minimum threshold are not included to the final score.

Ukrainian