Computer Simulation: A Foundational Approach Using Python

by Yahya Esmail Osais

Overview

Computer simulation is an effective and popular universal tool that can be applied to almost all disciplines. Requiring only basic knowledge of programming, mathematics, and probability theory, Computer Simulation: A Foundational Approach Using Python takes a hands-on approach to programming to introduce the fundamentals of computer simulation.

The main target of the book is computer science and engineering students who are interested mainly in directly applying the techniques to their research problems. The book will be of great interest to senior undergraduate and starting graduate students in the fields of computer science and engineering and industrial engineering.

Product Details

ISBN-13:	9781498726825
Publisher:	Taylor & Francis
Publication date:	11/17/2017
Series:	Chapman & Hall/CRC Computer and Information Science Series
Pages:	314
Product dimensions:	6.12(w) x 9.19(h) x (d)

About the Author

Yahya E. Osais is a faculty in the department of computer engineering at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. He obtained his B.Sc. and M.Sc. from the same department in 2000 and 2003, respectively. In 2010, he obtained his Ph.D. from the department of systems and computer engineering at Carleton university, Ontario, Canada. Dr. Osais regulary teaches a graduate course on computer simulation for students in the college of computer science and engineering at KFUPM. He also teaches courses on computer engineering design and web technologies. His current research interest includes stochastic modeling and simulation, cyberphysical systems, and Internet of things.

Table of Contents

Part I The Fundamentals. Chapter 1 Introduction. Chapter 2 Building Conceptual Models. Chapter 3 Simulating Probabilities. Chapter 4 Simulating Random Variables and Stochastic Processes. Chapter 5 Simulating the SingleServer Queueing System. Chapter 6 Statistical Analysis of Simulated Data. Part II Managing Complexity. Chapter 7 Event Graphs. Chapter 8 Building Simulation Programs. Part III Problem-Solving. Chapter 9 The Monte Carlo Method. Part IV Sources Of Randomness. Chapter 10 Random Variate Generation. Chapter 11 Random Number Generation. Part V Case Studies.Chapter 12 Case Studies

Editorial Reviews

"This book is highly recommended for a graduate course in modeling and simulation. It is also recommended for an introductory course in modeling and simulation for a senior undergraduate course. In addition, it can be a good reference for researchers, working engineers and scientists who work in modeling and simulation and optimization. It is a good addition to the field of modeling and simulation. I hope you will enjoy the book as much as I have enjoyed reviewing it."
—Mohammad S. Obaidat, Past President of the Society for Modeling and Simulation International, SCS, and Editor-in-Chief, International Journal of Communication Systems

From the Publisher