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Author : Bahar Kaynar
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (476 download)
Download or read book The Cross-entropy Method with Patching for Rare-event Simulation of Large Markov Chains written by Bahar Kaynar and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Bahar Kaynar
Publisher :
ISBN 13 :
Total Pages : 23 pages
Book Rating : 4.:/5 (453 download)
Download or read book The Cross-entropy Method with Patching for Rare-event Simulation of Large Markov Chains written by Bahar Kaynar and published by . This book was released on 2009 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Rostislav Man
Publisher :
ISBN 13 :
Total Pages : 96 pages
Book Rating : 4.:/5 (87 download)
Download or read book Rare Event Simulation for Heavy-tailed Distributions Using Cross-entropy Method written by Rostislav Man and published by . This book was released on 2003 with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher : ScholarlyEditions
ISBN 13 : 1464965633
Total Pages : 1080 pages
Book Rating : 4.4/5 (649 download)
Download or read book Issues in Industrial Relations and Management: 2011 Edition written by and published by ScholarlyEditions. This book was released on 2012-01-09 with total page 1080 pages. Available in PDF, EPUB and Kindle. Book excerpt: Issues in Industrial Relations and Management: 2011 Edition is a ScholarlyEditions™ eBook that delivers timely, authoritative, and comprehensive information about Industrial Relations and Management. The editors have built Issues in Industrial Relations and Management: 2011 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Industrial Relations and Management in this eBook to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Industrial Relations and Management: 2011 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.
Author : Hamed Fazlollahtabar
Publisher : Springer
ISBN 13 : 3319147471
Total Pages : 209 pages
Book Rating : 4.3/5 (191 download)
Download or read book Autonomous Guided Vehicles written by Hamed Fazlollahtabar and published by Springer. This book was released on 2015-01-21 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with extensive information on path planning optimization for both single and multiple Autonomous Guided Vehicles (AGVs), and discusses practical issues involved in advanced industrial applications of AGVs. After discussing previously published research in the field and highlighting the current gaps, it introduces new models developed by the authors with the goal of reducing costs and increasing productivity and effectiveness in the manufacturing industry. The new models address the increasing complexity of manufacturing networks, due for example to the adoption of flexible manufacturing systems that involve automated material handling systems, robots, numerically controlled machine tools, and automated inspection stations, while also considering the uncertainty and stochastic nature of automated equipment such as AGVs. The book discusses and provides solutions to important issues concerning the use of AGVs in the manufacturing industry, including material flow optimization with AGVs, programming manufacturing systems equipped with AGVs, reliability models, the reliability of AGVs, routing under uncertainty, and risks involved in AGV-based transportation. The clear style and straightforward descriptions of problems and their solutions make the book an excellent resource for graduate students. Moreover, thanks to its practice-oriented approach, the novelty of the findings and the contemporary topic it reports on, the book offers new stimulus for researchers and practitioners in the broad field of production engineering.
Author : Gerardo Rubino
Publisher : John Wiley & Sons
ISBN 13 : 9780470745410
Total Pages : 278 pages
Book Rating : 4.7/5 (454 download)
Download or read book Rare Event Simulation using Monte Carlo Methods written by Gerardo Rubino and published by John Wiley & Sons. This book was released on 2009-03-18 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a probabilistic model, a rare event is an event with a very small probability of occurrence. The forecasting of rare events is a formidable task but is important in many areas. For instance a catastrophic failure in a transport system or in a nuclear power plant, the failure of an information processing system in a bank, or in the communication network of a group of banks, leading to financial losses. Being able to evaluate the probability of rare events is therefore a critical issue. Monte Carlo Methods, the simulation of corresponding models, are used to analyze rare events. This book sets out to present the mathematical tools available for the efficient simulation of rare events. Importance sampling and splitting are presented along with an exposition of how to apply these tools to a variety of fields ranging from performance and dependability evaluation of complex systems, typically in computer science or in telecommunications, to chemical reaction analysis in biology or particle transport in physics. Graduate students, researchers and practitioners who wish to learn and apply rare event simulation techniques will find this book beneficial.
Author : Zdravko Botev
Publisher :
ISBN 13 :
Total Pages : 26 pages
Book Rating : 4.:/5 (13 download)
Download or read book Semiparametric Cross Entropy for Rare-Event Simulation written by Zdravko Botev and published by . This book was released on 2013 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Cross Entropy method is a well-known adaptive importance sampling method for rare-event probability estimation, which requires estimating an optimal importance sampling density within a parametric class. In this article we estimate an optimal importance sampling density within a wider semiparametric class of distributions. We show that this semiparametric version of the Cross Entropy method frequently yields efficient estimators. We illustrate the excellent practical performance of the method with numerical experiments and show that for the problems we consider it typically outperforms alternative schemes by orders of magnitude.
Author :
Publisher :
ISBN 13 :
Total Pages : 248 pages
Book Rating : 4.F/5 ( download)
Download or read book The Cross-entropy Method for Combinatorial Optimization, Rare Event Simulation and Neural Computation written by and published by . This book was released on 2005 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Alexandre Scott
Publisher :
ISBN 13 :
Total Pages : 230 pages
Book Rating : 4.:/5 (17 download)
Download or read book Extensions of the Cross-entropy Method with Applications to Diffusion Processes and Portfolio Losses written by Alexandre Scott and published by . This book was released on 2015 with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rare event simulation is a crucial part of simulations. In nancial mathematics, the study of rare events appear naturally when we consider risk measures such as the conditional value at risk. This thesis is composed of three related papers treating the rare event simulations subject: the rst paper addresses rare event simulations for di usion processes, the second paper addresses rare event simulations for the normal and the Student t-copula model while the last paper addresses rare event simulations for a portfolio model where there is a correlation structure between the loss-given- default and the probability of default.
Author : Reuven Y. Rubinstein
Publisher : John Wiley & Sons
ISBN 13 : 1118632389
Total Pages : 470 pages
Book Rating : 4.1/5 (186 download)
Download or read book Simulation and the Monte Carlo Method written by Reuven Y. Rubinstein and published by John Wiley & Sons. This book was released on 2016-10-21 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible new edition explores the major topics in Monte Carlo simulation that have arisen over the past 30 years and presents a sound foundation for problem solving Simulation and the Monte Carlo Method, Third Edition reflects the latest developments in the field and presents a fully updated and comprehensive account of the state-of-the-art theory, methods and applications that have emerged in Monte Carlo simulation since the publication of the classic First Edition over more than a quarter of a century ago. While maintaining its accessible and intuitive approach, this revised edition features a wealth of up-to-date information that facilitates a deeper understanding of problem solving across a wide array of subject areas, such as engineering, statistics, computer science, mathematics, and the physical and life sciences. The book begins with a modernized introduction that addresses the basic concepts of probability, Markov processes, and convex optimization. Subsequent chapters discuss the dramatic changes that have occurred in the field of the Monte Carlo method, with coverage of many modern topics including: Markov Chain Monte Carlo, variance reduction techniques such as importance (re-)sampling, and the transform likelihood ratio method, the score function method for sensitivity analysis, the stochastic approximation method and the stochastic counter-part method for Monte Carlo optimization, the cross-entropy method for rare events estimation and combinatorial optimization, and application of Monte Carlo techniques for counting problems. An extensive range of exercises is provided at the end of each chapter, as well as a generous sampling of applied examples. The Third Edition features a new chapter on the highly versatile splitting method, with applications to rare-event estimation, counting, sampling, and optimization. A second new chapter introduces the stochastic enumeration method, which is a new fast sequential Monte Carlo method for tree search. In addition, the Third Edition features new material on: • Random number generation, including multiple-recursive generators and the Mersenne Twister • Simulation of Gaussian processes, Brownian motion, and diffusion processes • Multilevel Monte Carlo method • New enhancements of the cross-entropy (CE) method, including the “improved” CE method, which uses sampling from the zero-variance distribution to find the optimal importance sampling parameters • Over 100 algorithms in modern pseudo code with flow control • Over 25 new exercises Simulation and the Monte Carlo Method, Third Edition is an excellent text for upper-undergraduate and beginning graduate courses in stochastic simulation and Monte Carlo techniques. The book also serves as a valuable reference for professionals who would like to achieve a more formal understanding of the Monte Carlo method. Reuven Y. Rubinstein, DSc, was Professor Emeritus in the Faculty of Industrial Engineering and Management at Technion-Israel Institute of Technology. He served as a consultant at numerous large-scale organizations, such as IBM, Motorola, and NEC. The author of over 100 articles and six books, Dr. Rubinstein was also the inventor of the popular score-function method in simulation analysis and generic cross-entropy methods for combinatorial optimization and counting. Dirk P. Kroese, PhD, is a Professor of Mathematics and Statistics in the School of Mathematics and Physics of The University of Queensland, Australia. He has published over 100 articles and four books in a wide range of areas in applied probability and statistics, including Monte Carlo methods, cross-entropy, randomized algorithms, tele-traffic c theory, reliability, computational statistics, applied probability, and stochastic modeling.
Author : Reuven Y. Rubinstein
Publisher : Springer Science & Business Media
ISBN 13 : 1475743211
Total Pages : 316 pages
Book Rating : 4.4/5 (757 download)
Download or read book The Cross-Entropy Method written by Reuven Y. Rubinstein and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rubinstein is the pioneer of the well-known score function and cross-entropy methods. Accessible to a broad audience of engineers, computer scientists, mathematicians, statisticians and in general anyone, theorist and practitioner, who is interested in smart simulation, fast optimization, learning algorithms, and image processing.
Download or read book Collection of Pamphlets Relating to Zoology and written by and published by . This book was released on 1873 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Reuven Y. Rubinstein
Publisher :
ISBN 13 : 9781475743227
Total Pages : 324 pages
Book Rating : 4.7/5 (432 download)
Download or read book The Cross-Entropy Method written by Reuven Y. Rubinstein and published by . This book was released on 2014-01-15 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author :
Publisher :
ISBN 13 : 9789175954042
Total Pages : 109 pages
Book Rating : 4.9/5 (54 download)
Download or read book Rare-event Simulation with Markov Chain Monte Carlo written by and published by . This book was released on 2015 with total page 109 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Hamed Nikbakht
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (119 download)
Download or read book Hamiltonian Markov Chain Monte Carlo Schemes for Rare Event Estimation written by Hamed Nikbakht and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimating rare event probabilities is a commonly encountered important problem in several engineering and scientific applications, most often observed in the form of probability of failure (PF) estimation or, alternatively and better sounding for the public, reliability estimation. In many practical applications, such as for structures, airplanes, mechanical equipment, and many more, failure probabilities are fortunately very low, from 10-4 to even 10-9 and less. Such estimations are of utmost importance for design choices, emergency preparedness, safety regulations, maintenance suggestions and more. Calculating such small numbers with accuracy however presents many numerical and mathematical challenges. To make matters worse, these estimations in realistic applications are usually based on high dimensional random spaces with numerous random variables and processes involved. A single simulation of such a model, or else a single model call, may also require several minutes to hours of computing time. As such, reducing the number of model calls is of great importance in these problems and one of the critical parameters that limits or prohibits use of several available techniques in the literature. This research is motivated by efficiently and precisely quantifying these probabilities, often encountered in reliability analysis of complex engineering systems, based on a developed framework termed Approximate Sampling Target with Postprocessing Adjustment (ASTPA), which herein is integrated with and supported by gradient-based Hamiltonian Markov Chain Monte Carlo (HMCMC) methods. Hamiltonian Markov Chain Monte Carlo sampling is characterized by much better scalability, faster mixing rates, is capable of generating samples with much weaker auto-correlation, even in complex high-dimensional parameter spaces, and has enjoyed broad-spectrum successes in most general settings. HMCMC adopts physical system dynamics, rather than a proposal probability distribution, and can be used to produce distant proposal samples for the integrated Metropolis step, thereby avoiding the slow exploration of the state space that results from the diffusive behavior of simple random-walk proposals. In this work, we aim to advance knowledge on Hamiltonian Markov Chain Monte Carlo methods, in general, with particular emphasis on its efficient utilization for rare event probability estimation in both Gaussian and Non-Gaussian spaces. This research also seeks to offer significant advancements in probabilistic inference and reliability predictions. Thus, in this context, we develop various Quasi-Newton based HMCMC schemes, which can sample very adeptly, particularly in difficult cases of high curvature, high-dimensionality and very small failure probabilities. The methodology is formally introduced, and the key theoretical aspects, and the underlying assumptions are discussed. Performance of the proposed methodology is then compared against state-of-the-art Subset Simulation in a series of challenging static and dynamic (time-dependent reliability) low- and high-dimensional benchmark problems. In the last phase of this work, with an aim to avoid using analytical gradients, within the proposed HMCMC-based framework, we investigate application of the Automatic Differentiation (AD) technique. In addition, to avoid use of gradients altogether and to improve the performance of the original SuS algorithm, we study the application of Quasi-Newton based HMCMC within the Subset Simulation framework. Various numerical examples are then presented to showcase the performance of the aforementioned approaches.
Author : Indira Kuruganti
Publisher :
ISBN 13 :
Total Pages : 392 pages
Book Rating : 4.:/5 (647 download)
Download or read book Optimal Importance Sampling for Simulating Rare Events in Markov Chains written by Indira Kuruganti and published by . This book was released on 1997 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Paul A. Gagniuc
Publisher : John Wiley & Sons
ISBN 13 : 1119387558
Total Pages : 252 pages
Book Rating : 4.1/5 (193 download)
Download or read book Markov Chains written by Paul A. Gagniuc and published by John Wiley & Sons. This book was released on 2017-07-31 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: A fascinating and instructive guide to Markov chains for experienced users and newcomers alike This unique guide to Markov chains approaches the subject along the four convergent lines of mathematics, implementation, simulation, and experimentation. It introduces readers to the art of stochastic modeling, shows how to design computer implementations, and provides extensive worked examples with case studies. Markov Chains: From Theory to Implementation and Experimentation begins with a general introduction to the history of probability theory in which the author uses quantifiable examples to illustrate how probability theory arrived at the concept of discrete-time and the Markov model from experiments involving independent variables. An introduction to simple stochastic matrices and transition probabilities is followed by a simulation of a two-state Markov chain. The notion of steady state is explored in connection with the long-run distribution behavior of the Markov chain. Predictions based on Markov chains with more than two states are examined, followed by a discussion of the notion of absorbing Markov chains. Also covered in detail are topics relating to the average time spent in a state, various chain configurations, and n-state Markov chain simulations used for verifying experiments involving various diagram configurations. • Fascinating historical notes shed light on the key ideas that led to the development of the Markov model and its variants • Various configurations of Markov Chains and their limitations are explored at length • Numerous examples—from basic to complex—are presented in a comparative manner using a variety of color graphics • All algorithms presented can be analyzed in either Visual Basic, Java Script, or PHP • Designed to be useful to professional statisticians as well as readers without extensive knowledge of probability theory Covering both the theory underlying the Markov model and an array of Markov chain implementations, within a common conceptual framework, Markov Chains: From Theory to Implementation and Experimentation is a stimulating introduction to and a valuable reference for those wishing to deepen their understanding of this extremely valuable statistical tool. Paul A. Gagniuc, PhD, is Associate Professor at Polytechnic University of Bucharest, Romania. He obtained his MS and his PhD in genetics at the University of Bucharest. Dr. Gagniuc’s work has been published in numerous high profile scientific journals, ranging from the Public Library of Science to BioMed Central and Nature journals. He is the recipient of several awards for exceptional scientific results and a highly active figure in the review process for different scientific areas.
