Infopaket

Fuzzy analysis

ДВС.2.06

Вибіркова дисципліна для ОП

First

2023/2024

8 Semester

5

LO 2. Be able to use basic principles and methods of mathematical, complex, and functional analysis, linear algebra and number theory, analytical geometry, and differential equations, including partial differential equations, probability theory, mathematical statistics and random processes, and numerical methods. LO 10. Be able to choose methods and algorithms rationally for solving optimization problems, operations research, optimal control and decision-making, and data analysis. PLO 24.2. Be able to apply professional knowledge, skills, and abilities in the field of applied mathematics and computer science for research of real processes of different natures.

Full-time form

1. Know basic concepts of mathematical analysis, linear algebra, discrete mathematics, differential equations, operations research, probability theory and mathematical statistics, and decision-making theory. 2. Be able to formulate and solve problems of linear programming, solve systems of linear algebraic equations with parameters, solve differential equations, investigate functions and functionals for extremum. 3. Possess the skills of building, analyzing, and applying mathematical models when solving applied problems.

Getting to know the research problems of solving problems of fuzzy mathematics; the necessary and sufficient conditions for solvability at the levels of goals, tasks, algorithms, and tools are given; solvability conditions for input, resource, and process under fuzzy conditions are determined. The course includes 2 content parts and 2 control papers. The discipline ends with an exam.

1. Voloshyn O.F., Mashchenko S.O. Modeli ta metody pryiniattia rishen: Navchalnyi posibnyk. – Kyiv: VPTs «Kyivskyi universytet», 2010. – 336 p. 2. Raskin L.G., Seraya O.V. Nechetkaya matematika: Uchebnoe posobie. – Kharkov: «Parus», 2008. – 352 p. 3. Snytiuk V.Ye. Prohnozuvannia. Modeli. Metody. Alhorytmy: Navchalnyi posibnyk. – Kyiv: «Maklaut», 2008. – 364 p. 4. Zaichenko Yu.P. Nechetkie modeli i metodi v intellektualnikh sistemakh: Uchebnoe posobie. – Kiev: « Slovo», 2008. – 344 p. 5. Snityuk V.E. Evolyutsionnie tekhnologii prinyatiya reshenii v usloviyakh neopredelennostiyu – K. : «MP Lesya», 2015. – 347 p. 6. Zgurovskii M.Z., Zaichenko Yu.P. Modeli i metodi prinyatiya reshenii v nechetkikh usloviyakh. – Kiev: «Naukova dumka», 2011. – 275 p.

Lectures, seminar classes, independent work.

Semester evaluation: The maximum number of points that can be obtained by a student is 60 points: Control worw No. 1: 20/12 points. Control work No. 2: 20/12 points. Oral answers: 20/12 points. Final evaluation (in the form of an exam): Maximum number of points that can be received by a student: 40 points. Form of conduct: written work. Types of tasks: 3 written tasks (2 theoretical questions and 1 practical task). The student receives an overall positive grade in the discipline if his grade for the exam is at least 24 (twenty-four) points. A student is admitted to the exam if during the semester he scores at least 36 points; and completes and passes 2 control works on time.

Ukrainian