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Reliability and Safety Analyses under Fuzziness by Takehisa Onisawa Pdf
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.
Linguistic Methods Under Fuzzy Information in System Safety and Reliability Analysis by Mohammad Yazdi Pdf
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.
Introduction to Fuzzy Reliability by Kai-Yuan Cai Pdf
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.
Computational Intelligence in Reliability Engineering by Gregory Levitin Pdf
This volume includes chapters presenting applications of different metaheuristics in reliability engineering, including ant colony optimization, great deluge algorithm, cross-entropy method and particle swarm optimization. It also presents chapters devoted to cellular automata and support vector machines, and applications of artificial neural networks, a powerful adaptive technique that can be used for learning, prediction and optimization. Several chapters describe aspects of imprecise reliability and applications of fuzzy and vague set theory.
Fuzzy Sets in Decision Analysis, Operations Research and Statistics by Roman Slowiński Pdf
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.
Fuzzy Evidence in Identification, Forecasting and Diagnosis by Alexander P. Rotshtein,Hanna B. Rakytyanska Pdf
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.
Handbook of Management under Uncertainty by Jaime Gil-Aluja Pdf
A mere few years ago it would have seemed odd to propose a Handbook on the treatment of management problems within a sphere of uncertainty. Even today, on the threshold of the third millennium, this statement may provoke a certain wariness. In fact, to resort to exact or random data, that is probable date, is quite normal and con venient, as we then know where we are going best, where we are proposing to go if all occurs as it is conceived and hoped for. To treat uncertain information, to accept a new principle and from there determined criteria, without being sure of oneself and confiding only in the will to better understand objects and phenomena, constitutes and compromise with a new form of understanding the behaviour of current beings that goes even further than simple rationality. Economic Science and particularly the use of its elements of configuration in the world of management, has imbued several generations with an analytical spirit that has given rise to the elaboration of theories widely accepted by the international scientific community. In this work we are proposing something a little more modest: to use, in the best possible way, data and information that are available for drawing up and applying techniques and instruments that are useful for current reality within the world of businesses and institutions, in an attempt to mislead ourselves as little as possible.
Handbook of Performability Engineering by Krishna B. Misra Pdf
Dependability and cost effectiveness are primarily seen as instruments for conducting international trade in the free market environment. These factors cannot be considered in isolation of each other. This handbook considers all aspects of performability engineering. The book provides a holistic view of the entire life cycle of activities of the product, along with the associated cost of environmental preservation at each stage, while maximizing the performance.
Intelligent Systems and Soft Computing for Nuclear Science and Industry by D Ruan,P D'hondt,E E Kerre Pdf
Following FLINS '94, the 1st International workshop on fuzzy logic and intelligent technologies in nuclear science, FLINS '96 aimed to introduce the principles of intelligent systems and soft computing, such as fuzzy logic, neural networks, genetic algorithms (and any combination of these three), knowledge-based expert systems and complex problem-solving techniques, in nuclear science and industry and in related fields. This volume presents carefully selected papers drawn from more than 20 countries. It covers theoretical aspects of intelligent systems and soft computing, together with their applications in nuclear science and industry. Contents:Fuzzy Algorithmic and Knowledge-Based Decision Support in Nuclear Engineering(H-J Zimmermann)Problem-Solving with Multiple Interdependent Criteria: Better Solutions to Complex Problems (C Carlsson & R Fullér)Functional Modelling for Integration of Human–Software–Hardware in Complex Physical Systems (M Modarres)Applying the Transferable Belief Model to Diagnostic Problems (P Smets)Application of Fuzzy Decision Making to Countermeasure Strategies After a Nuclear Accident (X Liu & D Ruan)A Fuzzy Control Algorithm for a Mobile Robot to Move Pass Obstacles (B-S Moon & J Lee)Experiments of Fuzzy Logic Control on a Nuclear Research Reactor (Z Liu & D Ruan)Intelligent Engineering and Technology for Nuclear Power Plant Operation (P P Wang & X L Gu)Improved Method for Incipient Multiple Fault Diagnosis with Application to Nuclear Power Plant (H-Y Chung et al)A Fuzzy Controller for NPPs (G H Schildt)Expert Environment for the Development of Nuclear Power Plants Failure Diagnosis Systems (P N Guido et al)Integrating Information in a Real-Time Data Visualization System on Nuclear Power Plant (E G Galdoz et al)and other papers Readership: Scientists and researchers in artificial intelligence, neural networks, fuzzy logic, robotics, software engineering, nuclear engineering, industrial chemistry, nuclear physics, mathematical physics, and applied mathematics. keywords:
Computing with Words in Information/Intelligent Systems 2 by Lotfi Zadeh Pdf
These two volumes consisting of Foundations and Applications provide the current status of theoretical and empirical developments in "computing with words". In philosophy, the twentieth century is said to be the century of language. This is mainly due to Wittgenstein who said: "The meaning of a word is its use in the language game". "The concept game is a concept with blurred edges". In the first phrase, "the language game" implies the everyday human activity with language, and in the latter, "game" simply implies an ordinary word. Thus, Wittgenstein precisely stated that a word is fuzzy in real life. Unfortunately this idea about a word was not accepted in the conventional science. We had to wait for Zadeh's fuzzy sets theory. Remembering Wittgenstein's statement, we should consider, on the one hand, the concept of "computing with words" from a philosophical point of view. It deeply relates to the everyday use of a word in which the meaning of a word is fuzzy in its nature.
Soft Computing for Risk Evaluation and Management by Da Ruan,Mario Fedrizzi Pdf
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.
Uncertainty Analysis in Engineering and Sciences: Fuzzy Logic, Statistics, and Neural Network Approach by Bilal M. Ayyub,Madan M. Gupta Pdf
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.
Fuzzy and Neuro-Fuzzy Systems in Medicine by Horia-Nicolai L Teodorescu,Abraham Kandel,Lakhmi C. Jain Pdf
Fuzzy and Neuro-Fuzzy Systems in Medicineprovides a thorough review of state-of-the-art techniques and practices, defines and explains relevant problems, as well as provides solutions to these problems. After an introduction, the book progresses from one topic to another - with a linear development from fundamentals to applications.
Advances in Soft Computing Applications by Shristi Kharola,Mangey Ram,Sachin K. Mangla,Yigit Kazancoglu Pdf
The proclivity of today’s technology to think like humans may be seen in new developing disciplines such as neural computing, fuzzy logic, evolutionary computation, machine learning, and probabilistic reasoning. These strategies are grouped together into one main technique known as "soft computing." This book discusses the most recent soft computing and fuzzy logic-based applications and innovations in industrial advancements, supply chain and logistics, system optimization, decision-making, artificial intelligence, smart systems, and other rapidly evolving technologies. In today’s competitive world, the book provides soft computing solutions to help companies overcome the obstacles posed by sophisticated decision-making systems.