Fuzzy Sets in Approximate Reasoning and Information Systems

Fuzzy Sets in Approximate Reasoning and Information Systems PDF Author: J.C. Bezdek
Publisher: Springer Science & Business Media
ISBN: 1461552435
Category : Mathematics
Languages : en
Pages : 527

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Book Description
Approximate reasoning is a key motivation in fuzzy sets and possibility theory. This volume provides a coherent view of this field, and its impact on database research and information retrieval. First, the semantic foundations of approximate reasoning are presented. Special emphasis is given to the representation of fuzzy rules and specialized types of approximate reasoning. Then syntactic aspects of approximate reasoning are surveyed and the algebraic underpinnings of fuzzy consequence relations are presented and explained. The second part of the book is devoted to inductive and neuro-fuzzy methods for learning fuzzy rules. It also contains new material on the application of possibility theory to data fusion. The last part of the book surveys the growing literature on fuzzy information systems. Each chapter contains extensive bibliographical material. Fuzzy Sets in Approximate Reasoning and Information Systems is a major source of information for research scholars and graduate students in computer science and artificial intelligence, interested in human information processing.

Fuzzy Sets in Approximate Reasoning and Information Systems

Fuzzy Sets in Approximate Reasoning and Information Systems PDF Author: J.C. Bezdek
Publisher: Springer Science & Business Media
ISBN: 1461552435
Category : Mathematics
Languages : en
Pages : 527

Get Book

Book Description
Approximate reasoning is a key motivation in fuzzy sets and possibility theory. This volume provides a coherent view of this field, and its impact on database research and information retrieval. First, the semantic foundations of approximate reasoning are presented. Special emphasis is given to the representation of fuzzy rules and specialized types of approximate reasoning. Then syntactic aspects of approximate reasoning are surveyed and the algebraic underpinnings of fuzzy consequence relations are presented and explained. The second part of the book is devoted to inductive and neuro-fuzzy methods for learning fuzzy rules. It also contains new material on the application of possibility theory to data fusion. The last part of the book surveys the growing literature on fuzzy information systems. Each chapter contains extensive bibliographical material. Fuzzy Sets in Approximate Reasoning and Information Systems is a major source of information for research scholars and graduate students in computer science and artificial intelligence, interested in human information processing.

An Introduction to Fuzzy Logic and Fuzzy Sets

An Introduction to Fuzzy Logic and Fuzzy Sets PDF Author: James J. Buckley
Publisher: Springer Science & Business Media
ISBN: 3790817996
Category : Computers
Languages : en
Pages : 287

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Book Description
This book is an excellent starting point for any curriculum in fuzzy systems fields such as computer science, mathematics, business/economics and engineering. It covers the basics leading to: fuzzy clustering, fuzzy pattern recognition, fuzzy database, fuzzy image processing, soft computing, fuzzy applications in operations research, fuzzy decision making, fuzzy rule based systems, fuzzy systems modeling, fuzzy mathematics. It is not a book designed for researchers - it is where you really learn the "basics" needed for any of the above-mentioned applications. It includes many figures and problem sets at the end of sections.

Fuzziness and Approximate Reasoning

Fuzziness and Approximate Reasoning PDF Author: K. K. Dompere
Publisher: Springer Science & Business Media
ISBN: 3540880860
Category : Computers
Languages : en
Pages : 311

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Book Description
This monograph is special in its orientation and contribution to current state of our understanding of decision-choice process and knowledge production. Its special orientation is to bring to the scientific community the discussions on the epistemic structure of the relationships among uncertainty, expectations, risk, possibility, probability and how the rules of fuzzy paradigm and the methods of fuzzy rationality bring new and different understanding to the relationships. At the level of theory of knowledge, it presents the structure and epistemic analysis of uncertainty, expectations and risk in decision-choice actions through the characteristics of substitution-transformation and input-output processes in categorial dynamics of actual-potential duality. The interactive effects of rationality and expectation are examined around belief, prospect, time and conditions of belief justification where the relationship between possibility and probability as a sequential link between potential and actual is analyzed to provide some understanding of the role of relative costs and benefits in defining risk in both nature and society. The concepts of possibilistic and probabilistic beliefs are explicated in relation to rationality and the decision-choice process where the analytical relationship between uncertainty and expectation formation is presented leading to the introduction of two types of uncertainty composed of fuzzy uncertainty and stochastic uncertainty.

Fuzzy Logic

Fuzzy Logic PDF Author: G. Gerla
Publisher: Springer Science & Business Media
ISBN: 9401596603
Category : Mathematics
Languages : en
Pages : 276

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Book Description
Fuzzy logic in narrow sense is a promising new chapter of formal logic whose basic ideas were formulated by Lotfi Zadeh (see Zadeh [1975]a). The aim of this theory is to formalize the "approximate reasoning" we use in everyday life, the object of investigation being the human aptitude to manage vague properties (as, for example, "beautiful", "small", "plausible", "believable", etc. ) that by their own nature can be satisfied to a degree different from 0 (false) and I (true). It is worth noting that the traditional deductive framework in many-valued logic is different from the one adopted in this book for fuzzy logic: in the former logics one always uses a "crisp" deduction apparatus, producing crisp sets of formulas, the formulas that are considered logically valid. By contrast, fuzzy logical deductive machinery is devised to produce a fuzzy set of formulas (the theorems) from a fuzzy set of formulas (the hypotheses). Approximate reasoning has generated a very interesting literature in recent years. However, in spite of several basic results, in our opinion, we are still far from a satisfactory setting of this very hard and mysterious subject. The aim of this book is to furnish some theoretical devices and to sketch a general framework for fuzzy logic. This is also in accordance with the non Fregean attitude of the book.

Fuzzy Implications

Fuzzy Implications PDF Author: Michał Baczyński
Publisher: Springer Science & Business Media
ISBN: 3540690808
Category : Computers
Languages : en
Pages : 311

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Book Description
This book is the first ever to deal exclusively with this class of operations. It offers an introduction to Fuzzy Implications, an analytical study of them, and an algebraic exploration into the structures that exist on the set of all FIs.

Approximate Reasoning by Parts

Approximate Reasoning by Parts PDF Author: Lech Polkowski
Publisher: Springer Science & Business Media
ISBN: 364222279X
Category : Technology & Engineering
Languages : en
Pages : 356

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Book Description
The monograph offers a view on Rough Mereology, a tool for reasoning under uncertainty, which goes back to Mereology, formulated in terms of parts by Lesniewski, and borrows from Fuzzy Set Theory and Rough Set Theory ideas of the containment to a degree. The result is a theory based on the notion of a part to a degree. One can invoke here a formula Rough: Rough Mereology : Mereology = Fuzzy Set Theory : Set Theory. As with Mereology, Rough Mereology finds important applications in problems of Spatial Reasoning, illustrated in this monograph with examples from Behavioral Robotics. Due to its involvement with concepts, Rough Mereology offers new approaches to Granular Computing, Classifier and Decision Synthesis, Logics for Information Systems, and are--formulation of well--known ideas of Neural Networks and Many Agent Systems. All these approaches are discussed in this monograph. To make the exposition self--contained, underlying notions of Set Theory, Topology, and Deductive and Reductive Reasoning with emphasis on Rough and Fuzzy Set Theories along with a thorough exposition of Mereology both in Lesniewski and Whitehead--Leonard--Goodman--Clarke versions are discussed at length. It is hoped that the monograph offers researchers in various areas of Artificial Intelligence a new tool to deal with analysis of relations among concepts.

Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications

Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications PDF Author: Marie-Jeanne Lesot
Publisher: Springer Nature
ISBN: 3030543412
Category : Technology & Engineering
Languages : en
Pages : 305

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Book Description
This book gathers cutting-edge papers in the area of Computational Intelligence, presented by specialists, and covering all major trends in the research community in order to provide readers with a rich primer. It presents an overview of various soft computing topics and approximate reasoning-based approaches, both from theoretical and applied perspectives. Numerous topics are covered: fundamentals aspects of fuzzy sets theory, reasoning approaches (interpolative, analogical, similarity-based), decision and optimization theory, fuzzy databases, soft machine learning, summarization, interpretability and XAI. Moreover, several application-based papers are included, e.g. on image processing, semantic web and intelligent tutoring systems. This book is dedicated to Bernadette Bouchon-Meunier in honor of her achievements in Computational Intelligence, which, throughout her career, have included profuse and diverse collaborations, both thematically and geographically.

Fuzziness and Approximate Reasoning

Fuzziness and Approximate Reasoning PDF Author: Kofi Kissi Dompere
Publisher: Springer
ISBN: 3540880879
Category : Mathematics
Languages : en
Pages : 311

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Book Description
We do not perceive the present as it is and in totality, nor do we infer the future from the present with any high degree of dependability, nor yet do we accurately know the consequences of our own actions. In addition, there is a fourth source of error to be taken into account, for we do not execute actions in the precise form in which they are imaged and willed. Frank H. Knight [R4.34, p. 202] The “degree” of certainty of confidence felt in the conclusion after it is reached cannot be ignored, for it is of the greatest practical signi- cance. The action which follows upon an opinion depends as much upon the amount of confidence in that opinion as it does upon fav- ableness of the opinion itself. The ultimate logic, or psychology, of these deliberations is obscure, a part of the scientifically unfathomable mystery of life and mind. Frank H. Knight [R4.34, p. 226-227] With some inaccuracy, description of uncertain consequences can be classified into two categories, those which use exclusively the language of probability distributions and those which call for some other principle, either to replace or supplement.

Approximate Reasoning in Decision Analysis

Approximate Reasoning in Decision Analysis PDF Author: Madan M. Gupta
Publisher: North Holland
ISBN:
Category : Business & Economics
Languages : en
Pages : 484

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Book Description


Similarity and Compatibility in Fuzzy Set Theory

Similarity and Compatibility in Fuzzy Set Theory PDF Author: Valerie V. Cross
Publisher: Physica
ISBN: 3790817937
Category : Mathematics
Languages : en
Pages : 207

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Book Description
Assessing the degree to which two objects, an object and a query, or two concepts are similar or compatible is a fundamental component of human reasoning and consequently is critical in the development of automated diagnosis, classification, information retrieval and decision systems. The assessment of similarity has played an important role in such diverse disciplines such as taxonomy, psychology, and the social sciences. Each discipline has proposed methods for quantifying similarity judgments suitable for its particular applications. This book presents a unified approach to quantifying similarity and compatibility within the framework of fuzzy set theory and examines the primary importance of these concepts in approximate reasoning. Examples of the application of similarity measures in various areas including expert systems, information retrieval, and intelligent database systems are provided.