Modeling and simulation

1.

Subject title

Modeling and simulation

Моделирање и симулација

2.

Code

F23L3S131

3.

Study program

Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Информатичка едукација, Software engineering and information systems, Примена на информациски технологии, Софтверско инженерство и информациски системи, Компјутерски науки, Компјутерско инженерство, Интернет, мрежи и безбедност, Software engineering and information systems, Стручни студии за програмирање, Стручни студии за програмирање,

4.

Organizer of the study program (unit, institute, department, division)

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Прв циклус

6.

Academic year / semester

4 / Летен

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Ласко Баснарков

9.

Prerequisites for enrollment

Веројатност и статистика или Основи на теорија на информации или Бизнис статистика или Математика 3

10.

Subject goals and competencies:

The student will acquire knowledge of using modeling techniques in order to evaluate the behavior of real systems. The student will acquire the ability to construct, verify and solve of models with different levels of abstraction and detail. It will also cover methods for fitting the state and parameters of models with real data, as well as predicting future behavior and "what-if" analyses.

11.

Subject content:

Lectures: 1. Introduction to modeling and simulation 2. Random number generation 3. Modeling of discrete systems 4. Modeling of continuous systems 5. Modeling of high-dimensional systems 6. Models with agents 7. Game theory models 8. Stochastic models and their application in finance 9. Waiting lines 10. Estimation of condition and parameters with real data and prediction of the future conduct 11. Optimization techniques 12. Methods for reducing dimensionality Exercises: 1. Getting to know Python 2. Random number generation 3. Representation and simulation of examples from discrete systems 4. Representation and simulation of examples from continuous systems 5. Representation and simulation of high-dimensional systems 6. Models with agents 7. Simulations with game theory 8. Stochastic models and their application in finance 9. Waiting lines 10. Application of several algorithms for estimation on a real situation and parameters with real data and prediction of future behavior 11. Optimization techniques 12. Methods for reducing dimensionality

12.

Learning methods:

Предавања поддржани со презентации преку слајдови, интерактивни предавања, вежби (користење на опрема и софтверски пакети), тимска работа, пример случаи, поканети гости предавачи, самостојна изработка и одбрана на проектна задача и семинарска работа, учење во електронско опкружување (форуми, консултации).

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

30 + 45 + 15 + 15 + 75 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

45 hours

16.

Other forms of activities

16.1.

Project tasks

15 hours

16.2.

Independent tasks

15 hours

16.3.

Homework

75 hours

17.

Grading method

17.1.

Tests

10 points

17.2.

Seminar work / project (presentation: written and oral)

15 points

17.3.

Activities and learning

10 points

17.4.

Final exam

70 points

18.

Grading criteria (points / grade)

up to 50 points

5 (five) (F)

from 51 to 60 points

6 (six) (E)

from 61 to 70 points

7 (seven) (D)

from 71 to 80 points

8 (eight) (C)

from 81 to 90 points

9 (nine) (B)

from 91 to 100 points

10 (ten) (A)

19.

Condition for signature and taking final exam

реализирани активности 15.1 и 15.2

20.

Language of instruction

македонски и англиски

21.

Quality assurance method

механизам на интерна евалуација и анкети

22.

Literature

22.1.

Mandatory literature

22.2.

Additional literature