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.
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.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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
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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