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More About This Textbook
Overview
Modeling and simulation has become an integral part of research and development across many fields of study, having evolved from a tool to a discipline in less than two decades. Modeling and Simulation Fundamentals offers a comprehensive and authoritative treatment of the topic and includes definitions, paradigms, and applications to equip readers with the skills needed to work successfully as developers and users of modeling and simulation.
Featuring contributions written by leading experts in the field, the book's fluid presentation builds from topic to topic and provides the foundation and theoretical underpinnings of modeling and simulation. First, an introduction to the topic is presented, including related terminology, examples of model development, and various domains of modeling and simulation. Subsequent chapters develop the necessary mathematical background needed to understand modeling and simulation topics, model types, and the importance of visualization. In addition, Monte Carlo simulation, continuous simulation, and discrete event simulation are thoroughly discussed, all of which are significant to a complete understanding of modeling and simulation. The book also features chapters that outline sophisticated methodologies, verification and validation, and the importance of interoperability. A related FTP site features color representations of the book's numerous figures.
Modeling and simulation Fundamentals encompasses a comprehensive study of the discipline and is an excellent book for modeling and simulation courses at the upper-undergraduate and graduate levels. It is also a valuable reference for researchers and practitioners in the fields of computational statistics, engineering, and computer science who use statistical modeling techniques.
Editorial Reviews
From the Publisher
"This text provides a well-designed overview of M&S as a discipline useful for graduate students with engineering, mathematics or computer science background and for specialists interested in fundamental principles of M&S, its further development and applications." (Zentralblatt MATH, 2010)Product Details
Meet the Author
JOHN A. SOKOLOWSKI, PhD, is Research Professor and Director of Research at the Virginia Modeling, Analysis and Simulation Center at Old Dominion University. He is the coeditor of Principles of Modeling and Simulation: A Multidisciplinary Approach and coauthor of Modeling and Simulation for Analyzing Global Events, both published by Wiley. Dr. Sokolowski currently focuses his research on computational modeling of human and social behavior.
CATHERINE M. BANKS, PhD, is Research Assistant Professor at the Virginia Modeling, Analysis and Simulation Center at Old Dominion University. She is the coeditor of Principles of Modeling and Simulation: A Multidisciplinary Approach and coauthor of Modeling and Simulation for Analyzing Global Events, both published by Wiley. Dr. Banks's current research interests include modeling states and their varied histories of revolution and insurgency, political economy and state volatility, and theoretical modeling concepts.
Table of Contents
Preface xi
Contributors xiii
1 Introduction to Modeling and Simulation Catherine M. Banks 1
M&S 2
M&S Characteristics and Descriptors 12
M&S Categories 19
Conclusion 22
References 24
2 Statistical Concepts for Discrete Event Simulation Roland R. Mielke 25
Probability 26
Simulation Basics 35
Input Data Modeling 39
Output Data Analysis 48
Conclusion 56
References 56
3 Discrete-Event Simulation Rafael Diaz Joshua G. Behr 57
Queuing System Model Components 60
Simulation Methodology 62
DES Example 65
Hand Simulation-Spreadsheet Implementation 67
Arena Simulation 87
Conclusion 97
References 98
4 Modeling Continuous Systems Wesley N. Colley 99
System Class 100
Modeling and Simulation (M&S) Strategy 101
Modeling Approach 102
Model Examples 104
Simulating Continuous Systems 110
Simulation Implementation 118
Conclusion 128
References 129
5 Monte Carlo Simulation John A. Sokolowski 131
The Monte Carlo Method 132
Sensitivity Analysis 142
Conclusion 145
References 145
6 Systems Modeling: Analysis and Operations Research Frederic D. McKenzie 147
System Model Types 147
Modeling Methodologies and Tools 148
Analysis of Modeling and Simulation (M&S) 165
OR Methods 174
Conclusion 179
References 179
Further Readings 180
7 Visualization Yuzhong Shen 181
Computer Graphics Fundamentals 182
Visualization Software and Tools 208
Case Studies 217
Conclusion 223
References 224
8 M&S Methodologies: A Systems Approach to the Social Sciences Barry G. Silverman Gnana K. Bharathy Benjamin Nye G. Jiyun Kim Mark Roddy Mjumbe Foe 227
Simulating State and Substate Actors with CountrySim: Synthesizing Theories Across the Social Sciences 229
The CountrySim Application and Sociocultural Game Results 255
Conclusions and the Way Forward 265
References 268
9 Modeling Human Behavior Yiannis Papelis Poornima Madhavan 271
Behavioral Modeling at the Physical Level 273
Behavioral Modeling at the Tactical and Strategic Level 274
Techniques for Human Behavior Modeling 277
Human Factors 305
Human-Computer Interaction 308
Conclusion 320
References 321
10 Verification, Validation, and Accreditation Mikel D. Petty 325
Motivation 326
Background Definitions 326
VV&A Definitions 330
V&V as Comparisons 332
Performing VV&A 333
V&V Methods 340
VV&A Case Studies 354
Conclusion 365
Acknowledgments 368
References 368
11 An Introduction to Distributed Simulation Gabriel A. Wainer Khaldoon Al-Zoubi 373
Trends and Challenges of Distributed Simulation 374
A Brief History of Distributed Simulation 375
Synchronization Algorithms for Parallel and Distributed Simulation 37
Distributed Simulation Middleware 383
Conclusion 397
References 398
12 Interoperability and Composability Andreas Tolk 403
Defining Interoperability and Composability 405
Current Interoperability Standard Solutions 412
Engineering Methods Supporting Interoperation and Composition 428
Conclusion 430
Reference 431
Further Readings 433
Index 435