Modern simulations and modeling

Modern simulations and modeling

1.

Subject title

Modern simulations and modeling

Модерни симулации и моделирање

2.

Code

m23_w_044

3.

Study program

IT management, Bioinformatics, Cloud Computing, Data science in computer science and engineering, Security, Cryptography and Coding, Еducation with ICT, Eco-informatics, Inteligent Systems, Internet Technologies and cyber security, Computer Science, Statistics and Data Analytics, Software for embedded systems, Software Engineering, Cloud Computing, IT management, Bioinformatics, Security, Cryptography and Coding, Statistics and Data Analytics, Software Engineering,

4.

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

Faculty of Information Sciences and Computer Engineering

5.

Study cycle (first, second, third)

Втор циклус

6.

Academic year / semester

5 / Зимски

7. Number of ECTS credits

6.0

8.

Instructor

проф. д-р Билјана Тојтовска Рибарски проф. д-р Марија Михова

9.

Prerequisites for enrollment

10.

Subject goals and competencies:


The purpose of the subject is to introduce students to the way mathematical models are built that describe different processes/structures. Famous probability -based models, statistics and graph theory - neuroscience, predator -prey models, stock market models, complex networks, etc. will be discussed.

11.

Subject content:


Generating random numbers. Stochastic processes. Brown movement, modeling with stochastic differential equations. Numerical algorithms for simulation of stochastic processes. Graph theory, random graphs. Application: - Stochastic neuronal networks; - Predator-Pray model - Complex networks studied through graph theory (eg internet, epidemics spread, computer virus spread, airports worldwide, social networks, etc.) - Models of financial instruments, interest rates (stock market math) ...

12.

Learning methods:


Предавања, вежби, проекти, семинарски, самостојно решавање на задачи

13.

Total available time fund

6.0 ECTS x 30 hours = 180 hours

14.

Time distribution

30 + 30 + 45 + 45 + 30 = 180 hours

15.

Forms of teaching activities

15.1.

Lectures - theoretical teaching

30 hours

15.2.

Exercises (laboratory, classroom), seminars, team work

30 hours

16.

Other forms of activities

16.1.

Project tasks

45 hours

16.2.

Independent tasks

45 hours

16.3.

Homework

30 hours

17.

Grading method

17.1.

Tests

60 points

17.2.

Seminar work / project (presentation: written and oral)

45 points

17.3.

Activities and learning

10 points

17.4.

Final exam

0 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

No.

Author

Title

Publisher

Year

6541

Sheldon M. Ross

Introduction to probability models

Academic Press, Elsevier

2014

6542

Bernt Oksendal

Stochastic differential equations

Springer

2010

6543

Albert-Laszlo Barabasi

Network Science

Cambridge University Press

2016

6544

Sergey N. Dorogovtsev

Lectures on Complex Networks

Oxford University press

2010

22.2.

Additional literature

No.

Author

Title

Publisher

Year