Yahya Esmail Osais

Computer Simulation

A Foundational Approach Using Python

• Gebundenes Buch

Produktbeschreibung

This book introduces the fundamentals of computer simulation using Python. Monte Carlo methods and applications are covered extensively, along with advanced topics, such as event graphs and the design of experiments.

Produktdetails

• Verlag: CRC Press
• Seitenzahl: 314
• Erscheinungstermin: 17. November 2017
• Englisch
• Abmessung: 241mm x 159mm x 22mm
• Gewicht: 592g
• ISBN-13: 9781498726825
• ISBN-10: 1498726828
• Artikelnr.: 50431624

Autorenporträt

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.

Inhaltsangabe

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

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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

Rezensionen

"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