Advances in type-2 fuzzy sets and systems : theory and applications
Author(s)
Bibliographic Information
Advances in type-2 fuzzy sets and systems : theory and applications
（Studies in fuzziness and soft computing, 301）
Springer, c2013
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
This book explores recent developments in the theoretical foundations and novel applications of general and interval type-2 fuzzy sets and systems, including: algebraic properties of type-2 fuzzy sets, geometric-based definition of type-2 fuzzy set operators, generalizations of the continuous KM algorithm, adaptiveness and novelty of interval type-2 fuzzy logic controllers, relations between conceptual spaces and type-2 fuzzy sets, type-2 fuzzy logic systems versus perceptual computers; modeling human perception of real world concepts with type-2 fuzzy sets, different methods for generating membership functions of interval and general type-2 fuzzy sets, and applications of interval type-2 fuzzy sets to control, machine tooling, image processing and diet. The applications demonstrate the appropriateness of using type-2 fuzzy sets and systems in real world problems that are characterized by different degrees of uncertainty.
Table of Contents
Part 1 - Theoretical Foundations.- Interval Type-2 Fuzzy Logic Systems and Perceptual Computers: Their Similarities and Differences.- Continuous Karnik-Mendel Algorithms and Their Generalizations.- Two Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers: Adaptiveness and Novelty.- Interval Type-2 Fuzzy Markov Chains.- zSlices Based General Type-2 Fuzzy Sets and Systems.- Geometric Type-2 Fuzzy Sets.- Type-2 Fuzzy Sets and Bichains.- Type-2 Fuzzy Sets and Conceptual Spaces.- Part B- Type-2 Fuzzy Set Membership Function Generation.- Modeling Complex Concepts with Type-2 Fuzzy Sets: The Case of User Satisfaction of Online Services.- Construction of Interval type-2 fuzzy sets from fuzzy sets. Methods and applications.- Interval type-2 fuzzy membership function generation methods for representing sample data.- Part C - Applications.- ype-2 Fuzzy Logic in Image Analysis and Pattern Recognition.- Reliable Tool Life Estimation with Multiple Acoustic Emission Signal Feature Selection and Integration Based on Type-2 Fuzzy Logic.- A Review of Cluster Validation with an Example of Type-2 Fuzzy Application in R.- Type-2 Fuzzy Set and Fuzzy Ontology for Diet Application.
by "Nielsen BookData"