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Knowledge-Based Simulation: Methodology and Application represents a recent compilation of research material that reviews fundamental concepts of simulation methodology and knowledge-based simulation applications. Knowledge-based simulation represents a new and exciting bridge area linking the fields of computer simulation and artificial intelligence. This book will appeal to both theorists and practitioners who require simulation to solve complex problems. A primary attraction of the book is its emphasis on both methodology and applications. In this way, the reader can explore new methods for encoding knowledge-inten- sive information into a simulation model, and new applications that utilize these methods.
Contributions from researchers and practitioners explore a spectrum of topics, including simulation software, parallel simulation techniques, knowledge-based simulations, simulation of neural nets, object-orientated simulation reuse of simulation models, and applications of simulation in areas such as architecture, manufacturing, LANs and others. These volumes are intended for a wide audience - those professionally involved in simulation research and applications, scholars and technical managers.
"Digital computer simulation helps study phenomena of great complexity, but how much do we know about the limits and possibilities of this new scientific practice? How do simulations compare to traditional experiments? And are they reliable? Scrutinizing these issues with a philosophical lens, Eric Winsberg explores the impact of simulation on such issues as the nature of scientific evidence, the role of values in science, the nature and role of fictions in science, and the relationship between simulation and experiment, theories and data, and theories at different levels of description"--Cover.
The objective of this publication is to comprehensively discuss the possibilities of producing steels with pre-determined attributes, demanded by the customer to fit exacting specifications. The information presented in the book has been designed to indicate the reasons for the expenses and to aid in the process of overcoming the difficulties and reducing the costs. In nine detailed chapters, the authors cover topics including: • steel as a major contributor to the economic wealth of a country in terms of its capabilities and production • current concerns of major steel producers • phenomena contributing to the quality of the product • information concerning the boundary conditions of the rolling process and initial conditions, put to use by mathematical models • the solid state incremental approach and flow formulation • parameters and variables - most of which make use of the exponential nature of phenomena that are activated by thermal energy • the application of three dimensional analysis to shape rolling • the evaluation of parameters by a form of inverse analysis to the flat rolling process • knowledge based modeling, using artificial intelligence, expert systems and neural networks They conclude that when either mathematical or physical modeling of the rolling process is considered and the aim is to satisfy the demands for customers, it is possible to produce what the customer wants, exactly.
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.
This volume contains the proceedings of the 2nd European Nuclear Simulation Symposium, held in Schliersee, FRG from October 22-24, 1990. The contributions cover research results and new developments in the fol- lowing areas: nuclear power plant simulation, software tools, artificial intelligence, neutron kinetics, plant analysers, computer based education, nuclear waste.
When it comes to discovering glitches inherent in complex systems-be it a railway or banking, chemical production, medical, manufacturing, or inventory control system-developing a simulation of a system can identify problems with less time, effort, and disruption than it would take to employ the original. Advantageous to both academic and industria
These transactions publish research in computer-based methods of computational collective intelligence (CCI) and their applications in a wide range of fields such as the Semantic Web, social networks, and multi-agent systems. TCCI strives to cover new methodological, theoretical and practical aspects of CCI understood as the form of intelligence that emerges from the collaboration and competition of many individuals (artificial and/or natural). The application of multiple computational intelligence technologies, such as fuzzy systems, evolutionary computation, neural systems, consensus theory, etc., aims to support human and other collective intelligence and to create new forms of CCI in natural and/or artificial systems. This tenth issue contains 13 carefully selected and thoroughly revised contributions.
This book constitutes the refereed post-proceedings of the third Asian Simulation Conference, AsiaSim 2004, held in Jeju Island, Korea in October 2004. The 78 revised full papers presented together with 2 invited keynote papers were carefully reviewed and selected from 178 submissions; after the conference, the papers went through another round of revision. The papers are organized in topical sections on modeling and simulation methodology, manufacturing, aerospace simulation, military simulation, medical simulation, general applications, network simulation and modeling, e-business simulation, numerical simulation, traffic simulation, transportation, virtual reality, engineering applications, and DEVS modeling and simulation.
Object-Oriented Simulation with Hierarchical, Modular Models: Intelligent Agents and Endomorphic Systems describes an approach to object-oriented discrete event simulation and the concepts of hierarchical, modular model construction, The implementation of the concepts of multifaceted modeling methodology in the DEVS-Scheme modeling and simulation environment is discussed. The use of the DEVS-Scheme environment in modeling artificial intelligent agents is also considered, along with the concept of endomorphism to characterize the application of self-embedded models, including models of self. Comprised of 15 chapters, this book begins with an overview of the dimensions of knowledge representation in simulation environments, followed by a discussion on object-oriented programming as well as the concepts of modular, hierarchical models and the system entity structure. Subsequent chapters focus on digraph-models and experimental frames; DEVS formalism and DEVS-Scheme simulation environment; a model base for simple multi-computer architectures; and rule-based specification of atomic models. Model bases in endomorphic systems and intelligent agents are also examined. This monograph will be of interest to simulation theorists as well as practitioners and researchers in the fields of artificial intelligence, systems engineering, computer science and engineering, and operations research.