Handbook of Research on Discrete Event Simulation Environments: Technologies and Applications | Date: 28 April 2011, 05:32
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Handbook of Research on Discrete Event Simulation Environments: Technologies and Applications
By Evon M. O. Abu-taieh, Asim Adbel Rahman El Sheikh
* Publisher: Information Science Reference
* Number Of Pages: 610
* Publication Date: 2009-10-20
* ISBN-10 / ASIN: 1605667749
* ISBN-13 / EAN: 9781605667744
Product Description:
Discrete event simulation environments have desirable features and components now driving researchers to develop and enhance existing environments. The Handbook of Research on Discrete Event Simulation Environments: Technologies and Applicationsprovides a comprehensive overview of theory and practice in simulation systems. A leading publication in this growing field, this Handbook of Research offers researchers, academicians, and practitioners progressive findings in simulation methodologies, modeling, standards, and applications.
Table of Contents:
Chapter I: Simulation – Body of Knowledge
Istvan Molnar, Bloomsburg University of Pennsylvania, Bloomsburg USA
Chapter 1, Simulation – Body of Knowledge, attempts to define the knowledge body of simulation and describes the underlying principles of simulation education. It argues that any programs in Modelling and Simulation should recognize the multi-and interdisciplinary character of the field and realize the program in wide co-operation. The paper starts with the clarification of the major objectives and principles of the Modelling and Simulation Program and the related degrees, based on a broad business and real world perspective. After reviewing students’ background, especially the communication, interpersonal, and team skills, the analytical and critical thinking skills, furthermore some of the additional skills leading to a career, the employer’s view and possible career paths are examined. Finally, the core knowledge body, the curriculum design and program related issues are discussed. The author hopes to contribute to the recent discussions about modelling and simulation education and the profession.
Chapter II: Simulation Environments as Vocational and Training Tools
Evon M. O. Abu-Taieh, Civil Aviation Regulatory Commission and Arab Academy For financial science, Amman, Jordan
Jeihan M. O. Abu-Tayeh, World Bank, Jordan
Chapter 2, Simulation Environments as Vocational and Training Tools, investigates over 50 simulation packages and simulators used in vocational and course training in many fields. Accordingly, the 50 simulation packages were categorized in the following fields: Pilot Training, Chemistry, Physics, Mathematics, Environment and ecological systems, Cosmology and astrophysics, Medicine and Surgery training, Cosmetic surgery, Engineering – Civil engineering, architecture, interior design, Computer and communication networks, Stock Market Analysis, Financial Models and Marketing, Military Training and Virtual Reality. The incentive for using simulation environments as vocational and training tools is to save live, money and effort.
Chapter III: Agent-Based Modeling: A Historical Perspective and a Review of Validation and Verification Efforts
Brian L. Heath, Wright State University, Dayton, USA
Raymond R. Hill, Air Force Institute of Technology, USA
Chapter 3, Agent-Based Modeling: A Historical Perspective and a Review of Validation and Verification Efforts, traces the historical roots of agent-based modeling. This review examines the modern influences of systems thinking, cybernetics as well as chaos and complexity on the growth of agent-based modeling. The chapter then examines the philosophical foundations of simulation verification and validation. Simulation verification and validation can be viewed from two quite different perspectives: the simulation philosopher and the simulation practitioner. Personnel from either camp are typically unaware of the other camp’s view of simulation verification and validation. This chapter examines both camps while also providing a survey of the literature and efforts pertaining to the verification and validation of agent-based models.
Chapter IV: Verification and Validation of Simulation Models
Sattar J Aboud, Middle East University for Graduate Studies, Amman-Jordan
Mohammad AL-Fayoumi, Middle East University for Graduate Studies, Amman-Jordan
Mohamed Alnuaimi, Middle East University for Graduate Studies, Amman-Jordan
Chapter 4, Verification and Validation of Simulation Models, discusses validation and verification of simulation models. The different approaches to deciding model validity are presented; how model validation and verification relate to the model development process are discussed; various validation techniques are defined; conceptual model validity, model verification, operational validity, and data validity; superior verification and validation technique for simulation models relied on a multistage approach are described; ways to document results are given; and a recommended procedure is presented.
Chapter V: DEVS-Based Simulation Interoperability
Thomas Wutzler, Max Planck Institute for Biogeochemistry, Germany
Hessam Sarjoughian, Arizona Center for Integrative Modeling and Simulation, USA
Chapter 5, DEVS-based simulation interoperability, introduces the usage of DEVS for the purpose of implementing interoperability across heterogeneous simulation models. It shows that the DEVS framework provides a simple, yet effective conceptual basis for handling simulation interoperability. It discusses the various useful properties of the DEVS framework, describes the Shared Abstract Model (SAM) approach for interoperating simulation models, and compares it to other approaches. The DEVS approach enables formal model specification with component models implemented in multiple programming languages. The simplicity of the integration of component models designed in the DEVS, DTSS, and DESS simulation formalisms and implemented in the programming languages Java and C++ is demonstrated by a basic educational example and by a real world forest carbon accounting model. The authors hope, that readers will appreciate the combination of generalness and simplicity and that readers will consider using the DEVS approach for simulation interoperability in their own projects.
Chapter VI: Experimental Error Measurement in Monte Carlo Simulation
Lucia Cassettari, University of Genoa, ITALY
Roberto Mosca, University of Genoa, ITALY
Roberto Revetria, University of Genoa, ITALY
Chapter 6, Experimental Error Measurement in Monte Carlo Simulation, describes the set up step series, developed by the Genoa Research Group on Production System Simulation at the beginning of the ’80s, as a sequence, through which it is possible at first statistically validate the simulator, then estimate the variables which effectively affect the different target functions, then obtain, through the regression meta-models, the relations linking the independent variables to the dependent ones (target functions) and, finally, proceed to the detection of the optimal functioning conditions. The authors pay great attention to the treatment, the evaluation and control of the Experimental Error, under the form of Mean Square Pure Error (MSPE), a measurement which is always culpably neglected in the traditional experimentation on the simulation models but, that potentially can consistently invalidate with its magnitude the value of the results obtained from the model.
Chapter VII: Efficient Discrete Simulation of Coded Wireless Communication Systems
Pedro J. A. Sebastiao, Instituto de Telecomunicacoes, Portugal
Francisco A. B. Cercas Instituto de Telecomunicacoes, Portugal
Adolfo V. T. Cartaxo, Instituto de Telecomunicacoes, Portugal
Chapter 7, Efficient Discrete Simulation of Coded Wireless Communication Systems, presents a simulation method, named Accelerated Simulation Method (ASM), that provides a high degree of efficiency and accuracy, namely for lower BER, wher
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