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Author: A. Dubi
Publisher: John Wiley & Sons
ISBN:
Category : Mathematics
Languages : en
Pages : 294
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Book Description
Focusses on the industry and use of mathematical methods, in particular the Monte Carlo method as a tool that can support and improve the engineering of systems. The application of the Monte Carlo method to system engineering is a new concept and the Monte Carlo method allows serious mathematical treatment of real-world industrial systems. This book which includes a large number of worked examples from real industrial problems, will prove a valuable reference source for students, researchers and engineers. It presents a unified approach to time-dependent system behavior in which the Monte Carlo method serves as a tool to obtain solutions to real-world challenges. The author suggest that efficiency can be increased through this integrated approach which combines previously independent considerations such as product reliability, maintenance requirements and the availability of spare parts. Features include: * Comprehensive coverage of the basic theory behind systems engineering and the Monte Carlo method enabling the reader to understand the concepts involved * Description of the method from the basic estimation of simple statistical processes, through the evaluation of multidimensional integrals to the solution of complex transport equations * Extensive examples detailing practical industrial applications for each of the techniques presented * Accompanying software (available via ftp) relating to specific examples which allows the reader to use the methods described to solve practical problems * Discussion of a variety of analytical tools from classical probabilistic methods to the concepts of event distribution, aging and Markovian methods explaining how these fit into the general systems engineering framework.
Author: A. Dubi
Publisher: John Wiley & Sons
ISBN:
Category : Mathematics
Languages : en
Pages : 294
Get Book Here
Book Description
Focusses on the industry and use of mathematical methods, in particular the Monte Carlo method as a tool that can support and improve the engineering of systems. The application of the Monte Carlo method to system engineering is a new concept and the Monte Carlo method allows serious mathematical treatment of real-world industrial systems. This book which includes a large number of worked examples from real industrial problems, will prove a valuable reference source for students, researchers and engineers. It presents a unified approach to time-dependent system behavior in which the Monte Carlo method serves as a tool to obtain solutions to real-world challenges. The author suggest that efficiency can be increased through this integrated approach which combines previously independent considerations such as product reliability, maintenance requirements and the availability of spare parts. Features include: * Comprehensive coverage of the basic theory behind systems engineering and the Monte Carlo method enabling the reader to understand the concepts involved * Description of the method from the basic estimation of simple statistical processes, through the evaluation of multidimensional integrals to the solution of complex transport equations * Extensive examples detailing practical industrial applications for each of the techniques presented * Accompanying software (available via ftp) relating to specific examples which allows the reader to use the methods described to solve practical problems * Discussion of a variety of analytical tools from classical probabilistic methods to the concepts of event distribution, aging and Markovian methods explaining how these fit into the general systems engineering framework.
Author: Enrico Zio
Publisher: Springer Science & Business Media
ISBN: 1447145887
Category : Technology & Engineering
Languages : en
Pages : 204
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Book Description
Monte Carlo simulation is one of the best tools for performing realistic analysis of complex systems as it allows most of the limiting assumptions on system behavior to be relaxed. The Monte Carlo Simulation Method for System Reliability and Risk Analysis comprehensively illustrates the Monte Carlo simulation method and its application to reliability and system engineering. Readers are given a sound understanding of the fundamentals of Monte Carlo sampling and simulation and its application for realistic system modeling. Whilst many of the topics rely on a high-level understanding of calculus, probability and statistics, simple academic examples will be provided in support to the explanation of the theoretical foundations to facilitate comprehension of the subject matter. Case studies will be introduced to provide the practical value of the most advanced techniques. This detailed approach makes The Monte Carlo Simulation Method for System Reliability and Risk Analysis a key reference for senior undergraduate and graduate students as well as researchers and practitioners. It provides a powerful tool for all those involved in system analysis for reliability, maintenance and risk evaluations.
Author: Margaret L. Loper
Publisher: Springer
ISBN: 144715634X
Category : Computers
Languages : en
Pages : 405
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Book Description
This easy to read text provides a broad introduction to the fundamental concepts of modeling and simulation (M&S) and systems engineering, highlighting how M&S is used across the entire systems engineering lifecycle. Features: reviews the full breadth of technologies, methodologies and uses of M&S, rather than just focusing on a specific aspect of the field; presents contributions from specialists in each topic covered; introduces the foundational elements and processes that serve as the groundwork for understanding M&S; explores common methods and methodologies used in M&S; discusses how best to design and execute experiments, covering the use of Monte Carlo techniques, surrogate modeling and distributed simulation; explores the use of M&S throughout the systems development lifecycle, describing a number of methods, techniques, and tools available to support systems engineering processes; provides a selection of case studies illustrating the use of M&S in systems engineering across a variety of domains.
Author: Billinton
Publisher: Springer Science & Business Media
ISBN: 1489913467
Category : Technology & Engineering
Languages : en
Pages : 361
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Book Description
The application of quantitative reliability evaluation in electric power sys tems has now evolved to the point at which most utilities use these techniques in one or more areas of their planning, design, and operation. Most of the techniques in use are based on analytical models and resulting analytical evaluation procedures. Improvements in and availability of high-speed digi tal computers have created the opportunity to analyze many of these prob lems using stochastic simulation methods and over the last decade there has been increased interest in and use made of Monte Carlo simulation in quantitative power system reliability assessment. Monte Carlo simulation is not a new concept and recorded applications have existed for at least 50 yr. However, localized high-speed computers with large-capacity storage have made Monte Carlo simulation an available and sometimes preferable option for many power system reliability applications. Monte Carlo simulation is also an integral part of a modern undergrad uate or graduate course on reliability evaluation of general engineering systems or specialized areas such as electric power systems. It is hoped that this textbook will help formalize the many existing applications of Monte Carlo simulation and assist in their integration in teaching programs. This book presents the basic concepts associated with Monte Carlo simulation.
Author: Paul Glasserman
Publisher: Springer Science & Business Media
ISBN: 0387216170
Category : Mathematics
Languages : en
Pages : 603
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Book Description
From the reviews: "Paul Glasserman has written an astonishingly good book that bridges financial engineering and the Monte Carlo method. The book will appeal to graduate students, researchers, and most of all, practicing financial engineers [...] So often, financial engineering texts are very theoretical. This book is not." --Glyn Holton, Contingency Analysis
Author: A. Dubi
Publisher:
ISBN: 9781904848004
Category : Monte Carlo method
Languages : en
Pages : 164
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Book Description
Author: Paolo Brandimarte
Publisher: John Wiley & Sons
ISBN: 1118594517
Category : Business & Economics
Languages : en
Pages : 620
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Book Description
An accessible treatment of Monte Carlo methods, techniques, and applications in the field of finance and economics Providing readers with an in-depth and comprehensive guide, the Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics presents a timely account of the applicationsof Monte Carlo methods in financial engineering and economics. Written by an international leading expert in thefield, the handbook illustrates the challenges confronting present-day financial practitioners and provides various applicationsof Monte Carlo techniques to answer these issues. The book is organized into five parts: introduction andmotivation; input analysis, modeling, and estimation; random variate and sample path generation; output analysisand variance reduction; and applications ranging from option pricing and risk management to optimization. The Handbook in Monte Carlo Simulation features: An introductory section for basic material on stochastic modeling and estimation aimed at readers who may need a summary or review of the essentials Carefully crafted examples in order to spot potential pitfalls and drawbacks of each approach An accessible treatment of advanced topics such as low-discrepancy sequences, stochastic optimization, dynamic programming, risk measures, and Markov chain Monte Carlo methods Numerous pieces of R code used to illustrate fundamental ideas in concrete terms and encourage experimentation The Handbook in Monte Carlo Simulation: Applications in Financial Engineering, Risk Management, and Economics is a complete reference for practitioners in the fields of finance, business, applied statistics, econometrics, and engineering, as well as a supplement for MBA and graduate-level courses on Monte Carlo methods and simulation.
Author: Dirk P. Kroese
Publisher: John Wiley & Sons
ISBN: 1118014952
Category : Mathematics
Languages : en
Pages : 627
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Book Description
A comprehensive overview of Monte Carlo simulation that explores the latest topics, techniques, and real-world applications More and more of today’s numerical problems found in engineering and finance are solved through Monte Carlo methods. The heightened popularity of these methods and their continuing development makes it important for researchers to have a comprehensive understanding of the Monte Carlo approach. Handbook of Monte Carlo Methods provides the theory, algorithms, and applications that helps provide a thorough understanding of the emerging dynamics of this rapidly-growing field. The authors begin with a discussion of fundamentals such as how to generate random numbers on a computer. Subsequent chapters discuss key Monte Carlo topics and methods, including: Random variable and stochastic process generation Markov chain Monte Carlo, featuring key algorithms such as the Metropolis-Hastings method, the Gibbs sampler, and hit-and-run Discrete-event simulation Techniques for the statistical analysis of simulation data including the delta method, steady-state estimation, and kernel density estimation Variance reduction, including importance sampling, latin hypercube sampling, and conditional Monte Carlo Estimation of derivatives and sensitivity analysis Advanced topics including cross-entropy, rare events, kernel density estimation, quasi Monte Carlo, particle systems, and randomized optimization The presented theoretical concepts are illustrated with worked examples that use MATLAB®, a related Web site houses the MATLAB® code, allowing readers to work hands-on with the material and also features the author's own lecture notes on Monte Carlo methods. Detailed appendices provide background material on probability theory, stochastic processes, and mathematical statistics as well as the key optimization concepts and techniques that are relevant to Monte Carlo simulation. Handbook of Monte Carlo Methods is an excellent reference for applied statisticians and practitioners working in the fields of engineering and finance who use or would like to learn how to use Monte Carlo in their research. It is also a suitable supplement for courses on Monte Carlo methods and computational statistics at the upper-undergraduate and graduate levels.
Author: Ivan T. Dimov
Publisher: World Scientific
ISBN: 9810223293
Category : Science
Languages : en
Pages : 308
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Book Description
The Monte Carlo method is inherently parallel and the extensive and rapid development in parallel computers, computational clusters and grids has resulted in renewed and increasing interest in this method. At the same time there has been an expansion in the application areas and the method is now widely used in many important areas of science including nuclear and semiconductor physics, statistical mechanics and heat and mass transfer.This book attempts to bridge the gap between theory and practice concentrating on modern algorithmic implementation on parallel architecture machines. Although a suitable text for final year postgraduate mathematicians and computational scientists it is principally aimed at the applied scientists: only a small amount of mathematical knowledge is assumed and theorem proving is kept to a minimum, with the main focus being on parallel algorithms development often to applied industrial problems.A selection of algorithms developed both for serial and parallel machines are provided.
Author: Larry B. Rainey
Publisher: John Wiley & Sons
ISBN: 1118460316
Category : Mathematics
Languages : en
Pages : 638
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Book Description
“...a much-needed handbook with contributions from well-chosen practitioners. A primary accomplishment is to provide guidance for those involved in modeling and simulation in support of Systems of Systems development, more particularly guidance that draws on well-conceived academic research to define concepts and terms, that identifies primary challenges for developers, and that suggests fruitful approaches grounded in theory and successful examples.” Paul Davis, The RAND Corporation Modeling and Simulation Support for System of Systems Engineering Applications provides a comprehensive overview of the underlying theory, methods, and solutions in modeling and simulation support for system of systems engineering. Highlighting plentiful multidisciplinary applications of modeling and simulation, the book uniquely addresses the criteria and challenges found within the field. Beginning with a foundation of concepts, terms, and categories, a theoretical and generalized approach to system of systems engineering is introduced, and real-world applications via case studies and examples are presented. A unified approach is maintained in an effort to understand the complexity of a single system as well as the context among other proximate systems. In addition, the book features: Cutting edge coverage of modeling and simulation within the field of system of systems, including transportation, system health management, space mission analysis, systems engineering methodology, and energy State-of-the-art advances within multiple domains to instantiate theoretic insights, applicable methods, and lessons learned from real-world applications of modeling and simulation The challenges of system of systems engineering using a systematic and holistic approach Key concepts, terms, and activities to provide a comprehensive, unified, and concise representation of the field A collection of chapters written by over 40 recognized international experts from academia, government, and industry A research agenda derived from the contribution of experts that guides scholars and researchers towards open questions Modeling and Simulation Support for System of Systems Engineering Applications is an ideal reference and resource for academics and practitioners in operations research, engineering, statistics, mathematics, modeling and simulation, and computer science. The book is also an excellent course book for graduate and PhD-level courses in modeling and simulation, engineering, and computer science.
