Systems Modeling

Faculty: Faculty of Engineering
Department(s): IE
Course: Systems Modeling
Weekly hours: Theory: 2 Exercises: 2
ECTS Credits: 6
Semester: Spring

Lecture Schedule:

Tuesday (Lectures - Avtocomanda, Classroom 403) : 11:15 - 13:00
Tuesday (Exercises - Avtocomanda, Computer Lab) : 13:30 - 15:15

Lecturer: Dr. Hiqmet Kamberaj
Room Number: 409
Phone Number of the lecturer: +389 (0)23174010 (ext. 123)
E-mail address of the lecturer: km.ude.ubi|jarebmakh#km.ude.ubi|jarebmakh

Course Objectives:

The aim of the course is to provide knowledge on the development of simulation system models and ability to develop a simulation model for a given problem. This course provides the main concepts of modelling, which are state and state space, models of computation, concurrency, communication, modelling of data and time. The goal is to relate these concepts to applications and show the impact of the fundamental concepts on the potential and limitations of application techniques and tools, such as synthesis, performance analysis, formal verification, etc.

Learning Outcomes:

After completing this course, students will be able to:

  1. Model a process and design of computer simulation model.
  2. Use the random number generator in a simulation model.
  3. Use random variable generator in a simulation model.
  4. Learn how to analyze simulation output using statistics.
  5. Verify and validate a simulation model.
  6. Learn how to compare system configurations for statistical analysis purposes.
Skill outcomes Necessary ( + ) Not Necessary ( –)
Written communication skills +
Oral communication skills +
Computer skills +
Working in laboratory +
Working team +
Preparing projects +
Knowledge of foreign language +
Scientific and professional literature analysis +
Problem solving skills +
Management skills +
Presentation skills +

Course Textbooks:

  1. F.L. Severance. System Modeling and Simulation. An Introduction.John Wiley & Sons, LTD, 2001.
  2. Law, A.M., and W.D. Kelton, “Simulation Modelling and Analysis”, McGraw Hill, Singapore (2000).
  3. Harrel, C.R., et. al., “System Improvement Using Simulation”, 3rd edition, JMI Consulting Group and ProModel Corporation (1995).
Teaching methods Ideal %
Teaching ex cathedra (teacher as the figure of authority, standing in front of the class and lecturing) 80
Interactive teaching (ask questions in class, assign and check homework, or hold class or group discussions) 10
Mentor teaching (consultant-teacher who has a supervisory responsibility and supervising the students) -
Laboratory work -
Seminar work -
Field Work (enables students to examine the theories and the practical experiences of a particular discipline interact) -
Semester project 5
Case Study (An in-depth exploration of a particular context) -
Students Team work 5


  • Students are obliged to attend at least 10 weeks out of 14 weeks of lectures, exercises, and other activities (72%).
  • The teaching staff should monitor and submit Course Attendance Report to the Student Affairs Office at the end of 14th week of each semester.
  • The attendance rule for failed overlapping courses is %36 (5 weeks) and for non-overlapping courses is 57% (8 weeks);
  • The attendance rule for course from upper semester is 57% (8 weeks).
  • Students are not obliged to attend the course if the course is double repeated. However, they need to register and to pay repeated course.

Exams (Mid-Term Exam, Final Exam, Make-up Exam):

There are two exams, the Mid-Term and Final Exam, at the middle and at the end of the semester, respectively. The students, who do not earn minimum 50 credit points from the Mid-Term, Final Exam including Homework Assignments, have to take the Make-Up Exam, which counts only for Final Exam credit points. The terms of the exams are defined by the Academic Calendar announced on the University web site.

Passing Score:

The maximum number of credit points is collected during the semester, as follows: Mid-term Exam = 40 Credit Points (minimum requirement is 10CPs - midterm + activity - to enter Final Exam), Final Exam (minimum requirement is 25 % to pass) = 40 Credit Points. Homeworks, quizzes, specific assignments and term papers = 20 Credit Points (minimum requirement is 5 credit points to enter Final Exam). Total=100.

Weekly Study Plan

Weeks Topics
1 Introduction to the philosophy of this course. Introduction to Systems Modelling.
2 Event driven models.
3 System characterization and simulation diagrams.
4 Dynamic systems: Euler and Taylor’s method.
5 Dynamic systems: Runge-Kutta methods. Higher order systems.
6 Stochastic generators: Uniform random numbers U(0,1) and their statistical properties.
7 Mid term review - discussion - 2 CPs of activity.
- Mid Term Exam Week
8 Generation of non-uniform random variates.
9 Characterizing random processes.
10 Discrete systems.
11 Modelling time-driven systems: Modelling Input Signals, Nomenclature.
12 Modelling time-driven systems: Discrete delays, distributed delays, system integration.
13 Markov processes: Probabilistic systems and Discrete-time Markov processes.
14 Final exam review - discussion - 3 CPs of activity.
- Final exam week.

Student workload:

For calculating the Total Student Work Load we multiply the course ECTS credits with standard figure 30. (ECTS Credit: 6) x 30 = 180 hours.

Activities Hours
Lecture hours for 14 weeks: 28
Laboratory and class exercises for 14 weeks: 28
Student Mentoring for 14 weeks: -
Consultation for 14 weeks: 4
Exam preparations and exam hours (Midterm, final, Makeups) Exam preparations and exam hours: Each one should be at least minimum 10 hours. 30
Individual reading work for 14 weeks (Reading assignments/expectations for reading and comprehension is 5 pages per hour. Example: If a book 300 pages, total Individual reading work for 14 weeks 300:5 = 60 hours. 50
Homework and work practice for 14 weeks: 40
Preparation of diploma work, for 14 weeks: -
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