fuzzy reasoning applications (25 Ergebnisse)

Zustand: Fair. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Clean from markings. In fair condition, suitable as a study copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:0124677509.

Zustand: Good. Most items will be dispatched the same or the next working day. A copy that has been read but remains in clean condition. All of the pages are intact and the cover is intact and the spine may show signs of wear. The book may have minor markings which are not specifically mentioned.

.- London - New York - Toronto - Sydney - San Francisco. 1981. Academic Press Limited. 4º menor. XVIII- 381 pgs. Con ilustraciones. Cartoné editorial. Unas pocas frases subrayadas rotulador transparente. Firma anterior poseedor. Buen estado. . . ISBN 10: 0124677509. Informática.

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Hardcover. Zustand: Brand New. 317 pages. 9.25x6.10x0.94 inches. In Stock.

Taschenbuch. Zustand: Neu. Fuzzy Approaches for Soft Computing and Approximate Reasoning: Theories and Applications | Dedicated to Bernadette Bouchon-Meunier | Marie-Jeanne Lesot (u. a.) | Taschenbuch | Studies in Fuzziness and Soft Computing | xx | Englisch | 2021 | Springer | EAN 9783030543433 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Taschenbuch. Zustand: Neu. Techniques of Decision Making, Uncertain Reasoning and Regression Analysis Under the Hesitant Fuzzy Environment and Their Applications | Chenyang Song (u. a.) | Taschenbuch | xii | Englisch | 2022 | Springer | EAN 9789811658020 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book mainly introduces some techniques of decision-making, uncertain reasoning and regression analysis under the hesitant fuzzy environment and expands the applications of hesitant fuzzy sets in solving practical problems. The book pursues three major objectives: (1) to introduce some techniques about decision-making, uncertain reasoning and regression analysis under the hesitant fuzzy environment, (2) to prove these techniques theoretically and (3) to apply the involved techniques to practical problems. The book is especially valuable for readers to understand how hesitant fuzzy set could be employed in decision-making, uncertain reasoning and regression analysis and motivates researchers to expand more application fields of hesitant fuzzy set.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book mainly introduces some techniques of decision-making, uncertain reasoning and regression analysis under the hesitant fuzzy environment and expands the applications of hesitant fuzzy sets in solving practical problems. The book pursues three major objectives: (1) to introduce some techniques about decision-making, uncertain reasoning and regression analysis under the hesitant fuzzy environment, (2) to prove these techniques theoretically and (3) to apply the involved techniques to practical problems. The book is especially valuable for readers to understand how hesitant fuzzy set could be employed in decision-making, uncertain reasoning and regression analysis and motivates researchers to expand more application fields of hesitant fuzzy set.

Taschenbuch. Zustand: Neu. Fuzzy Rule-Based Inference | Advances and Applications in Reasoning with Approximate Knowledge Interpolation | Fangyi Li (u. a.) | Taschenbuch | xiv | Englisch | 2025 | Springer | EAN 9789819704934 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book covers a comprehensive approach to the development and application of a suite of novel algorithms for practical approximate knowledge-based inference. It includes an introduction to the fundamental concepts of fuzzy sets, fuzzy logic, and fuzzy inference. Collectively, this book provides a systematic tutorial and self-contained reference to recent advances in the field of fuzzy rule-based inference. Approximate reasoning systems facilitate inference by utilizing fuzzy if-then production rules for decision-making under circumstances where knowledge is imprecisely characterized. Compositional rule of inference (CRI) and fuzzy rule interpolation (FRI) are two typical techniques used to implement such systems. The question of when to apply these potentially powerful reasoning techniques via automated computation procedures is often addressed by checking whether certain rules can match given observations. Both techniques have been widely investigated to enhance the performance of approximate reasoning. Increasingly more attention has been paid to the development of systems where rule antecedent attributes are associated with measures of their relative significance or weights. However, they are mostly implemented in isolation within their respective areas, making it difficult to achieve accurate reasoning when both techniques are required simultaneously. This book first addresses the issue of assigning equal significance to all antecedent attributes in the rules when deriving the consequents. It presents a suite of weighted algorithms for both CRI and FRI fuzzy inference mechanisms. This includes an innovative reverse engineering process that can derive attribute weightings from given rules, increasing the automation level of the resulting systems. An integrated fuzzy reasoning approach is then developed from these two sets of weighted improvements, showcasing more effective and efficient techniques for approximate reasoning. Additionally, the book provides an overarching application to interpretable medical risk analysis, thanks to the semantics-rich fuzzy rules with attribute values represented in linguistic terms. Moreover, it illustrates successful solutions to benchmark problems in the relevant literature, demonstrating the practicality of the systematic approach to weighted approximate reasoning.

Paperback. Zustand: Brand New. 188 pages. 9.25x6.10x0.51 inches. In Stock.

Hardcover. Zustand: Brand New. 176 pages. 9.50x6.25x0.75 inches. In Stock.

Hardcover. Zustand: Brand New. 405 pages. 9.50x6.50x1.00 inches. In Stock.

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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers a comprehensive approach to the development and application of a suite of novel algorithms for practical approximate knowledge-based inference. It includes an introduction to the fundamental concepts of fuzzy sets, fuzzy logic, and fuzzy inference. Collectively, this book provides a systematic tutorial and self-contained reference to recent advances in the field of fuzzy rule-based inference.Approximate reasoning systems facilitate inference by utilizing fuzzy if-then production rules for decision-making under circumstances where knowledge is imprecisely characterized. Compositional rule of inference (CRI) and fuzzy rule interpolation (FRI) are two typical techniques used to implement such systems. The question of when to apply these potentially powerful reasoning techniques via automated computation procedures is often addressed by checking whether certain rules can match given observations. Both techniques have been widely investigated to enhance the performance of approximate reasoning. Increasingly more attention has been paid to the development of systems where rule antecedent attributes are associated with measures of their relative significance or weights. However, they are mostly implemented in isolation within their respective areas, making it difficult to achieve accurate reasoning when both techniques are required simultaneously.This book first addresses the issue of assigning equal significance to all antecedent attributes in the rules when deriving the consequents. It presents a suite of weighted algorithms for both CRI and FRI fuzzy inference mechanisms. This includes an innovative reverse engineering process that can derive attribute weightings from given rules, increasing the automation level of the resulting systems. An integrated fuzzy reasoning approach is then developed from these two sets of weighted improvements, showcasing more effective and efficient techniques for approximate reasoning. Additionally, the book provides an overarching application to interpretable medical risk analysis, thanks to the semantics-rich fuzzy rules with attribute values represented in linguistic terms. Moreover, it illustrates successful solutions to benchmark problems in the relevant literature, demonstrating the practicality of the systematic approach to weighted approximate reasoning.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book covers a comprehensive approach to the development and application of a suite of novel algorithms for practical approximate knowledge-based inference. It includes an introduction to the fundamental concepts of fuzzy sets, fuzzy logic, and fuzzy inference. Collectively, this book provides a systematic tutorial and self-contained reference to recent advances in the field of fuzzy rule-based inference.Approximate reasoning systems facilitate inference by utilizing fuzzy if-then production rules for decision-making under circumstances where knowledge is imprecisely characterized. Compositional rule of inference (CRI) and fuzzy rule interpolation (FRI) are two typical techniques used to implement such systems. The question of when to apply these potentially powerful reasoning techniques via automated computation procedures is often addressed by checking whether certain rules can match given observations. Both techniques have been widely investigated to enhance the performance of approximate reasoning. Increasingly more attention has been paid to the development of systems where rule antecedent attributes are associated with measures of their relative significance or weights. However, they are mostly implemented in isolation within their respective areas, making it difficult to achieve accurate reasoning when both techniques are required simultaneously.This book first addresses the issue of assigning equal significance to all antecedent attributes in the rules when deriving the consequents. It presents a suite of weighted algorithms for both CRI and FRI fuzzy inference mechanisms. This includes an innovative reverse engineering process that can derive attribute weightings from given rules, increasing the automation level of the resulting systems. An integrated fuzzy reasoning approach is then developed from these two sets of weighted improvements, showcasing more effective and efficient techniques for approximate reasoning. Additionally, the book provides an overarching application to interpretable medical risk analysis, thanks to the semantics-rich fuzzy rules with attribute values represented in linguistic terms. Moreover, it illustrates successful solutions to benchmark problems in the relevant literature, demonstrating the practicality of the systematic approach to weighted approximate reasoning.

Hardcover. Zustand: Brand New. 201 pages. 9.26x6.11x9.21 inches. In Stock.

Buch. Zustand: Neu. Neuware - This book will be highly useful to researchers in the area of pattern classification and computer vision as well as for academics and professionals. Combining theory and practice, the book presents several experimental results, all synthetic and real data, are provided on a unified platform for pattern classification and object recognition.