Recent Developments in Fuzzy Logic and Fuzzy Sets: Dedicated to Lotfi A. Zadeh
Author:   Shahnaz N. Shahbazova ,  Michio Sugeno ,  Janusz Kacprzyk
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   391
ISBN:  

9783030388928


Pages:   211
Publication Date:   06 March 2020
Format:   Hardback
Availability:   Manufactured on demand   Availability explained
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Recent Developments in Fuzzy Logic and Fuzzy Sets: Dedicated to Lotfi A. Zadeh


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Overview

This book provides a timely and comprehensive overview of current theories and methods in fuzzy logic, as well as relevant applications in a variety of fields of science and technology. Dedicated to Lotfi A. Zadeh on his one year death anniversary, the book goes beyond a pure commemorative text. Yet, it offers a fresh perspective on a number of relevant topics, such as computing with words, theory of perceptions, possibility theory, and decision-making in a fuzzy environment. Written by Zadeh’s closest colleagues and friends, the different chapters are intended both as a timely reference guide and a source of inspiration for scientists, developers and researchers who have been dealing with fuzzy sets or would like to learn more about their potential for their future research.

Full Product Details

Author:   Shahnaz N. Shahbazova ,  Michio Sugeno ,  Janusz Kacprzyk
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   391
Weight:   0.500kg
ISBN:  

9783030388928


ISBN 10:   3030388921
Pages:   211
Publication Date:   06 March 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1: Fuzziness in Information Extracted from Tweets’ Hashtag and Keywords.- Chapter 2: Why Triangular and Trapezoid Membership Functions: A Simple Explanation.- Chapter 3: Probabilistic and More General Uncertainty-Based (e.g., Fuzzy) Approaches to Crisp Clustering Explain the Empirical Success of the K-Sets Algorithm.- Chapter 4: Statistical Approach to Fuzzy Cognitive Maps.- Chapter 5: Semi–Supervised Learning to Rank with Nonlinear Preference Model.

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