Lecture1_Intro_Modeling_Simulation (1).pptx

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1. Introduction to Modeling & Simulation Lecture 1 - BSIT Course

2. Learning Objectives Understand the meaning of system, model, and simulation Know why simulation is needed See applications of simulation in real life Get an overview of the course

3. What is a System? A group of connected parts working together Every system has input, process, output, and feedback Examples: hospital, banking, traffic system

4. System Analysis Study of a system to know how it works Find system purpose, components, and boundaries Understand environment that affects the system

5. Why Do We Need Models? Real systems are complex, costly, or risky Models are safe and easy to study Models allow repeatable experiments Example: flight simulator for pilot training

6. What is a Model? A simple version of a real system Only keeps important details Examples: map, equation, computer simulation

7. What is Simulation? Running a model to copy real-world behavior Used to predict, analyze, and improve systems Examples: weather forecast, traffic flow, flight training

8. System → Model → Simulation System = Real-world system Model = Simplified version of the system Simulation = Running the model on computer

9. Why Simulation? Safe – no risk to real system Cheap – saves money Fast – saves time Repeatable – same test can be done many times

10. Classification of Systems Natural vs. Man-made Deterministic vs. Stochastic Static vs. Dynamic Continuous vs. Discrete Open vs. Closed

11. Examples of System Types Traffic lights → Discrete, Dynamic Weather → Continuous, Stochastic Solar system → Deterministic, Continuous Banking → Man-made, Open, Dynamic

12. Advantages of Simulation Cost saving Risk free experiments Helps in decision making Can be applied in many fields

13. Limitations of Simulation Not 100% accurate Depends on data quality Sometimes expensive to run

14. Applications of Simulation Engineering – aircraft, cars Healthcare – hospital planning, disease spread Business – banks, call centers IT – computer networks, AI models

15. Summary System = connected parts with input, process, output Model = simplified version of system Simulation = running the model Simulation is useful but has limitations

16. Review Questions What is the difference between a system and a model? Give an example of deterministic and stochastic systems Why is simulation useful in IT?