Applied System Simulation

Simulation and molding are efficient techniques that can aid the city and regional planners and engineers in optimizing the operation of urban systems such as traffic light control, highway toll automation, consensus building, public safety, and environmental protection. When modeling transportation systems such as freeway systems, arterial or downtown grid systems, the city planner and engineer is concerned with capturing the varied interactions between drivers, automobiles, and the infrastructure. Modeling and simulation are used to effectively optimize the design and operation of all of these urban systems. It is possible that in an urban simulation community workshop, citizens can work interactively in front of computers and be able using the click of the mouse to walk up to their own front porch, looking at the proposed shopping mall alternatives across the street from virtually any angle and proposed bridge or tunnel and see how it can reduce traffic congestion. Buildings can be scaled down or taken out, their orientation can be changed in order to check the view and orientation in order to have better site with efficient energy-conservation. The stone or brick material on a building can be replaced by colored concrete, or more trees and lampposts can be placed on the site. Such flexibility in simulation and animation allows creative ideas in the design and orientation of urban sites to be demonstrated to citizens and decision makers before final realization.

APPLIED SIMULATION MODELING provides the student with both a conceptual introduction to the concepts of simulation modeling and practical experience with real examples using popular commercial simulation packages ARENA and @Risk. The coverage includes Risk Simulation, Dynamic Systems, and Discrete Event Simulation models. Throughout the text, the authors show readers how they can use simulation in the context of decision making. Practical examples from Operations Management, Manufacturing, Health Care, and Finance are included throughout to give students an appreciation for the wide scope of application and the robust nature of simulation modeling. Special student editions of ARENA and @Risk are packaged with the text.

The 2015 International Conference on Applied System Innovation (ICASI 2015) was held May 22-27, 2015 in Osaka, Japan and provided a unified communication platform for researchers active in a wide range of research fields. Professionals from industry, academia and government were encouraged to discourse on research and development, professional practice, business and management in the information, innovation, communication and engineering fields. This conference enabled interdisciplinary collaboration between science and engineering technologists in the academic and industry fields as well as networking internationally. The conference received 1063 submitted papers, whereby 421 papers were selected by the committees to be presented at the ICASI 2015 conference. These papers were divided into 13 Regular Sessions and 13 Invited Sessions, and presented in several parallel sessions. The ICASI 2015 committees selected 226 excellent papers for publication in this proceedings volume, covering topics ranging from information technology, innovation design, communication science and engineering, industrial design, creative design, applied mathematics, computer science, design theory and cultural and creative research to electrical and electronic engineering, mechanical and automation engineering, green technology and architecture engineering and material science, among others.

The Handbook of Applied System Science is organized around both methodological approaches in systems science, and the substantive topic to which these approaches have been applied. The volume begins with an essay that introduces three system science methods: agent-based modeling, system dynamics, and network analysis. The remainder of the volume is organized around three broad topics: (1) health and human development, (2) environment and sustainability, and (3) communities and social change. Each part begins with a brief introductory essay, and includes nine chapters that demonstrate the application of system science methods to address research questions in these areas. This handbook will be useful for work in Public Health, Sociology, Criminal Justice, Social Work, Political Science, Environmental Studies, Urban Studies, and Psychology.

The only singular, all-encompassing textbook on state-of-the-art technical performance evaluation Fundamentals of Performance Evaluation of Computer and Telecommunication Systems uniquely presents all techniques of performance evaluation of computers systems, communication networks, and telecommunications in a balanced manner. Written by the renowned Professor Mohammad S. Obaidat and his coauthor Professor Noureddine Boudriga, it is also the only resource to treat computer and telecommunication systems as inseparable issues. The authors explain the basic concepts of performance evaluation, applications, performance evaluation metrics, workload types, benchmarking, and characterization of workload. This is followed by a review of the basics of probability theory, and then, the main techniques for performance evaluation namely measurement, simulation, and analytic modeling with case studies and examples. Contains the practical and applicable knowledge necessary for a successful performance evaluation in a balanced approach Reviews measurement tools, benchmark programs, design of experiments, traffic models, basics of queueing theory, and operational and mean value analysis Covers the techniques for validation and verification of simulation as well as random number generation, random variate generation, and testing with examples Features numerous examples and case studies, as well as exercises and problems for use as homework or programming assignments Fundamentals of Performance Evaluation of Computer and Telecommunication Systems is an ideal textbook for graduate students in computer science, electrical engineering, computer engineering, and information sciences, technology, and systems. It is also an excellent reference for practicing engineers and scientists.

obtained by simulation more quickly, effec Computer simulation of dynamic systems is a topic which is growing steadily in importance tively and cheaply than by experimentation and testing of the real system. System perfor in the physical sciences, engineering, biology and medicine. The reasons for this trend mance can also be investigated using simula relate not only to the steadily increasing tion for a much wider range of conditions than can be contemplated for the real system power of computers and the rapidly falling costs of hardware, but also to the availability because of operating constraints or safety of appropriate software tools in the form of requirements. Similar factors can apply in simulation languages. Problem-oriented lan other fields, such as biomedical systems guages of this kind assist those who are not engineering. specialists in computational methods to trans System simulation, using digital computers, can relate either to models based on continu late a mathematical description into a simula tion program in a simple and straightforward ous variables or to discrete-event descriptions. fashion. They can also provide useful diag Continuous system simulation techniques are applied to systems described by sets of differ nostic information when difficulties are encountered. Therefore, a simulation lan ential equations and algebraic equations.

Not only do modeling and simulation help provide a better understanding of how real-world systems function, they also enable us to predict system behavior before a system is actually built and analyze systems accurately under varying operating conditions. Modeling and Simulation of Systems Using MATLAB® and Simulink® provides comprehensive, state-of-the-art coverage of all the important aspects of modeling and simulating both physical and conceptual systems. Various real-life examples show how simulation plays a key role in understanding real-world systems. The author also explains how to effectively use MATLAB and Simulink software to successfully apply the modeling and simulation techniques presented. After introducing the underlying philosophy of systems, the book offers step-by-step procedures for modeling different types of systems using modeling techniques, such as the graph-theoretic approach, interpretive structural modeling, and system dynamics modeling. It then explores how simulation evolved from pre-computer days into the current science of today. The text also presents modern soft computing techniques, including artificial neural networks, fuzzy systems, and genetic algorithms, for modeling and simulating complex and nonlinear systems. The final chapter addresses discrete systems modeling. Preparing both undergraduate and graduate students for advanced modeling and simulation courses, this text helps them carry out effective simulation studies. In addition, graduate students should be able to comprehend and conduct simulation research after completing this book.