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Reliability And Safety Analyses Under Fuzziness


Reliability And Safety Analyses Under Fuzziness
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Reliability And Safety Analyses Under Fuzziness


Reliability And Safety Analyses Under Fuzziness
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Author : Takehisa Onisawa
language : en
Publisher: Physica
Release Date : 2013-06-05

Reliability And Safety Analyses Under Fuzziness written by Takehisa Onisawa and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-05 with Technology & Engineering categories.


This book provides a comprehensive, up-to-date account on recent applications of fuzzy sets and possibility theory in reliability and safety analysis. Various aspects of system's reliability, quality control, reliability and safety of man-machine systems fault analysis, risk assessment and analysis, structural, seismic, safety, etc. are discussed. The book provides new tools for handling non-probabilistic aspects of uncertainty in these problems. It is the first in this field in the world literature.



Introduction To Fuzzy Reliability


Introduction To Fuzzy Reliability
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Author : Kai-Yuan Cai
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Introduction To Fuzzy Reliability written by Kai-Yuan Cai and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


Introduction to Fuzzy Reliability treats fuzzy methodology in hardware reliability and software reliability in a relatively systematic manner. The contents of this book are organized as follows. Chapter 1 places reliability engineering in the scope of a broader area, i.e. system failure engineering. Readers will find that although this book is confined to hardware and software reliability, it may be useful for other aspects of system failure engineering, like maintenance and quality control. Chapter 2 contains the elementary knowledge of fuzzy sets and possibility spaces which are required reading for the rest of this book. This chapter is included for the overall completeness of the book, but a few points (e.g. definition of conditional possibility and existence theorem of possibility space) may be new. Chapter 3 discusses how to calculate probist system reliability when the component reliabilities are represented by fuzzy numbers, and how to analyze fault trees when probabilities of basic events are fuzzy. Chapter 4 presents the basic theory of profust reliability, whereas Chapter 5 analyzes the profust reliability behavior of a number of engineering systems. Chapters 6 and 7 are devoted to probist reliability theory from two different perspectives. Chapter 8 discusses how to model software reliability behavior by using fuzzy methodology. Chapter 9 includes a number of mathematical problems which are raised by applications of fuzzy methodology in hardware and software reliability, but may be important for fuzzy set and possibility theories.



Linguistic Methods Under Fuzzy Information In System Safety And Reliability Analysis


Linguistic Methods Under Fuzzy Information In System Safety And Reliability Analysis
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Author : Mohammad Yazdi
language : en
Publisher: Springer Nature
Release Date : 2022-03-10

Linguistic Methods Under Fuzzy Information In System Safety And Reliability Analysis written by Mohammad Yazdi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-10 with Technology & Engineering categories.


This book reviews and presents a number of approaches to Fuzzy-based system safety and reliability assessment. For each proposed approach, it provides case studies demonstrating their applicability, which will enable readers to implement them into their own risk analysis process. The book begins by giving a review of using linguistic terms in system safety and reliability analysis methods and their extension by fuzzy sets. It then progresses in a logical fashion, dedicating a chapter to each approach, including the 2-tuple fuzzy-based linguistic term set approach, fuzzy bow-tie analysis, optimizing the allocation of risk control measures using fuzzy MCDM approach, fuzzy sets theory and human reliability, and emergency decision making fuzzy-expert aided disaster management system. This book will be of interest to professionals and researchers working in the field of system safety and reliability, as well as postgraduate and undergraduate students studying applications of fuzzy systems.



Fuzzy Evidence In Identification Forecasting And Diagnosis


Fuzzy Evidence In Identification Forecasting And Diagnosis
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Author : Alexander P. Rotshtein
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-27

Fuzzy Evidence In Identification Forecasting And Diagnosis written by Alexander P. Rotshtein and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-27 with Computers categories.


The purpose of this book is to present a methodology for designing and tuning fuzzy expert systems in order to identify nonlinear objects; that is, to build input-output models using expert and experimental information. The results of these identifications are used for direct and inverse fuzzy evidence in forecasting and diagnosis problem solving. The book is organised as follows: Chapter 1 presents the basic knowledge about fuzzy sets, genetic algorithms and neural nets necessary for a clear understanding of the rest of this book. Chapter 2 analyzes direct fuzzy inference based on fuzzy if-then rules. Chapter 3 is devoted to the tuning of fuzzy rules for direct inference using genetic algorithms and neural nets. Chapter 4 presents models and algorithms for extracting fuzzy rules from experimental data. Chapter 5 describes a method for solving fuzzy logic equations necessary for the inverse fuzzy inference in diagnostic systems. Chapters 6 and 7 are devoted to inverse fuzzy inference based on fuzzy relations and fuzzy rules. Chapter 8 presents a method for extracting fuzzy relations from data. All the algorithms presented in Chapters 2-8 are validated by computer experiments and illustrated by solving medical and technical forecasting and diagnosis problems. Finally, Chapter 9 includes applications of the proposed methodology in dynamic and inventory control systems, prediction of results of football games, decision making in road accident investigations, project management and reliability analysis.



Computational Intelligence In Reliability Engineering


Computational Intelligence In Reliability Engineering
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Author : Gregory Levitin
language : en
Publisher: Springer
Release Date : 2007-01-10

Computational Intelligence In Reliability Engineering written by Gregory Levitin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-01-10 with Technology & Engineering categories.


This two volume book covers the recent applications of computational intelli gence techniques in reliability engineering. Research in the area of computational intelligence is growing rapidly due to the many successful applications of these new techniques in very diverse problems. “Computational Intelligence” covers many fields such as neural networks, fu zzy logic, evolutionary computing, and their hybrids and derivatives. Many indus tries have benefited from adopting this technology. The increased number of patents and diverse range of products devel oped using computational intelligence methods is evidence of this fact. These techniques have attracted increasing attention in recent years for solving many complex problems. They are inspired by nature, biology, statistical tech niques, physics and neuroscience. They have been successfully applied in solving many complex problems where traditional problem solving methods have failed. The book aims to be a repository for the current and cutting edge applications of computational intelligent techniques in reliability analysis and optimization.



Fuzzy Sets In Decision Analysis Operations Research And Statistics


Fuzzy Sets In Decision Analysis Operations Research And Statistics
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Author : Roman Slowiński
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Fuzzy Sets In Decision Analysis Operations Research And Statistics written by Roman Slowiński and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.


Fuzzy Sets in Decision Analysis, Operations Research and Statistics includes chapters on fuzzy preference modeling, multiple criteria analysis, ranking and sorting methods, group decision-making and fuzzy game theory. It also presents optimization techniques such as fuzzy linear and non-linear programming, applications to graph problems and fuzzy combinatorial methods such as fuzzy dynamic programming. In addition, the book also accounts for advances in fuzzy data analysis, fuzzy statistics, and applications to reliability analysis. These topics are covered within four parts: Decision Making, Mathematical Programming, Statistics and Data Analysis, and Reliability, Maintenance and Replacement. The scope and content of the book has resulted from multiple interactions between the editor of the volume, the series editors, the series advisory board, and experts in each chapter area. Each chapter was written by a well-known researcher on the topic and reviewed by other experts in the area. These expert reviewers sometimes became co-authors because of the extent of their contribution to the chapter. As a result, twenty-five authors from twelve countries and four continents were involved in the creation of the 13 chapters, which enhances the international character of the project and gives an idea of how carefully the Handbook has been developed.



Reliability And Safety Analyses Under Fuzziness


Reliability And Safety Analyses Under Fuzziness
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Author : Takehisa Onisawa
language : en
Publisher:
Release Date : 2014-01-15

Reliability And Safety Analyses Under Fuzziness written by Takehisa Onisawa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-15 with categories.




Uncertainty Analysis In Engineering And Sciences Fuzzy Logic Statistics And Neural Network Approach


Uncertainty Analysis In Engineering And Sciences Fuzzy Logic Statistics And Neural Network Approach
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Author : Bilal M. Ayyub
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Uncertainty Analysis In Engineering And Sciences Fuzzy Logic Statistics And Neural Network Approach written by Bilal M. Ayyub and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.


Uncertainty has been of concern to engineers, managers and . scientists for many centuries. In management sciences there have existed definitions of uncertainty in a rather narrow sense since the beginning of this century. In engineering and uncertainty has for a long time been considered as in sciences, however, synonymous with random, stochastic, statistic, or probabilistic. Only since the early sixties views on uncertainty have ~ecome more heterogeneous and more tools to model uncertainty than statistics have been proposed by several scientists. The problem of modeling uncertainty adequately has become more important the more complex systems have become, the faster the scientific and engineering world develops, and the more important, but also more difficult, forecasting of future states of systems have become. The first question one should probably ask is whether uncertainty is a phenomenon, a feature of real world systems, a state of mind or a label for a situation in which a human being wants to make statements about phenomena, i. e. , reality, models, and theories, respectively. One cart also ask whether uncertainty is an objective fact or just a subjective impression which is closely related to individual persons. Whether uncertainty is an objective feature of physical real systems seems to be a philosophical question. This shall not be answered in this volume.



Soft Computing For Risk Evaluation And Management


Soft Computing For Risk Evaluation And Management
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Author : Da Ruan
language : en
Publisher: Physica
Release Date : 2012-08-10

Soft Computing For Risk Evaluation And Management written by Da Ruan and has been published by Physica this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-08-10 with Business & Economics categories.


Risk is a crucial element in virtually all problems people in diverse areas face in their activities. It is impossible to find adequate models and solutions without taking it into account. Due to uncertainty and complexity in those problems, traditional "hard" tools and techniques may be insufficient for their formulation and solution. This is the first book in the literature that shows how soft computing methods (fuzzy logic, neural networks, genetic algorithms, etc.) can be employed to deal with various problems related to risk analysis, evaluation and management in various fields of technology, environment and finance.



Statistical Methods For Fuzzy Data


Statistical Methods For Fuzzy Data
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Author : Reinhard Viertl
language : en
Publisher: John Wiley & Sons
Release Date : 2011-01-25

Statistical Methods For Fuzzy Data written by Reinhard Viertl and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-25 with Mathematics categories.


Statistical data are not always precise numbers, or vectors, or categories. Real data are frequently what is called fuzzy. Examples where this fuzziness is obvious are quality of life data, environmental, biological, medical, sociological and economics data. Also the results of measurements can be best described by using fuzzy numbers and fuzzy vectors respectively. Statistical analysis methods have to be adapted for the analysis of fuzzy data. In this book, the foundations of the description of fuzzy data are explained, including methods on how to obtain the characterizing function of fuzzy measurement results. Furthermore, statistical methods are then generalized to the analysis of fuzzy data and fuzzy a-priori information. Key Features: Provides basic methods for the mathematical description of fuzzy data, as well as statistical methods that can be used to analyze fuzzy data. Describes methods of increasing importance with applications in areas such as environmental statistics and social science. Complements the theory with exercises and solutions and is illustrated throughout with diagrams and examples. Explores areas such quantitative description of data uncertainty and mathematical description of fuzzy data. This work is aimed at statisticians working with fuzzy logic, engineering statisticians, finance researchers, and environmental statisticians. It is written for readers who are familiar with elementary stochastic models and basic statistical methods.