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This course provides an overview of simulation and modeling techniques for understanding, analyzing, and predicting the behavior of complex systems. Topics covered include different types of models, studying systems through experimentation, and when to use simulation.
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CPE 412 SIMULATION and MODELING • Instructor: Dr. Mahmoud Alrefaei • Various notes and transparencies can be found on web page. http://www.just.edu.jo/~alrefaei/cpe412.html
What is Simulation • Simulation is a realizationof a representation of larger and more complex activity. • An Activity is a system • Simulation uses model for representing the activity (system). • Realization means to make things look like real. • Example: Aircraft Simulator. Manufacturing System. Computer Networks, etc.
Alternative Definition • Simulation is pretending doing something in order to understand, analyze, and predict the future of systems behavior.
Systems and Models • System: is a set of interacting components or entities that interact together to achieve some task. • Examples of simulations include: • Hospitals • Telecommunications system • Highways • Computer Networks • Airport check in and Boarding facilities. • A Fast food restaurant.
The state of the system: is a collection of variables needed to describe the system at some point of time. • Discrete and Continuous systems: • Discrete: when the state variables change at discrete point of times. • Example: a Bank ( the number of customers in the bank change at discrete points when a customer arrives or departs) • Continuous: when the state variables change continuously. • Example: the quantity of fluid in a tank as it leaks
Models • A simplified representation of a system intended to enhance our ability to understand, predict, and possibly control the behavior of the system • It represents the most system components and the way they interact.
Types of Models • Physical models: Like a model of house, bridge, car, …etc • Mental models: Personal view of a foreign country, or an event or object. • Symbolic models: • Mathematical models • maps • graphs • words (as in newspaper) • pictures
How to Study Systems • Experiment with the actual system if possible • Experiment with a model of the system • Physical Model • Mathematical Model • Analytical Solution • Simulation
When to Use Simulation • The system does not exist. • Experimentation with real system is expensive • There is a need to study the past, present and the future behavior of the system in real time. • Mathematical Models are impossible. • Mathematical Models exist but have no analytical solution. • Results of Simulation are possible. • Expected accuracy of simulation results is consistent with the given problem.