Αποτελέσματα Αναζήτησης
Chapters 3 to 5 develop a three - part series of M & S paradigms, starting with Chapter 3 , “ Discrete - Event Simulation, ” Chapter 4 , “ Modeling Continuous Systems, ” and Chapter 5 , “ Monte Carlo Simulation. ” Chapters 6 and 7 develop two areas necessary for model development.
Lecture 2 - Modeling and Simulation • Model types: ODE, PDE, State Machines, Hybrid • Modeling approaches: – physics based (white box) – input-output models (black box) • Linear systems • Simulation • Modeling uncertainty
Lecture 9 – Modeling, Simulation, and Systems Engineering • Development steps • Model-based control engineering • Modeling and simulation • Systems platform: hardware, systems software.
The steps involved in developing a simulation model, designing a simulation experiment, and performing simulation analysis are: Step 1. Identify the problem. Step 2. Formulate the problem. Step 3. Collect and process real system data. Step 4. Formulate and develop a model. Step 5. Validate the model. Step 6. Document model for future use. Step 7.
Recently, modelling and simulation has been slated to become the computing paradigm of the future. As a paradigm, it is a way of representing problems and thinking about them, as much as a solution method. The problems span the analysis and design of complex dynamical systems.
• Comprehend important concepts in computer modeling and simulation. • Model uncertainty and randomness by means of statistical distributions. • Form a hypothesis and design a computer experiment to test it. • Collect and model data, estimate errors in the results and analyze simula-tion outputs.
Objectives of the Course. Introduce the main tools for the simulation of random variables and the approximation of multidimensional integrals: Integration by Monte Carlo, inversion method, transformation method, rejection sampling, importance sampling,
