Advances in Type-2 Fuzzy Sets and Systems
Subtitle: Theory and Applications
By: edited by Alireza Sadeghian, Jerry M. Mendel, Hooman Tahayori
Contributors: Mendel, Jerry M.; Tahayori, Hooman; SpringerLink (Online service)
Series: Studies in Fuzziness and Soft Computing -- 301
Publisher: Springer New York; Imprint: Springer
Published: 2013
Place of publication: New York, NY
Language: eng
Format: [electronic resource] :
Number of pages: 262
ISBN-13: 9781461466666
Subjects: Engineering; Computational intelligence; Artificial intelligence; Artificial Intelligence (incl. Robotics)
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: title: Part 1 - Theoretical Foundations; title: Interval Type-2 Fuzzy Logic Systems and Perceptual Computers: Their Similarities and Differences; title: Continuous Karnik-Mendel Algorithms and Their Generalizations; title: Two Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers: Adaptiveness and Novelty; title: Interval Type-2 Fuzzy Markov Chains; title: zSlices Based General Type-2 Fuzzy Sets and Systems; title: Geometric Type-2 Fuzzy Sets; title: Type-2 Fuzzy Sets and Bichains; title: Type-2 Fuzzy Sets and Conceptual Spaces; title: Part B- Type-2 Fuzzy Set Membership Function Generation; title: 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; title: Interval type-2 fuzzy membership function generation methods for representing sample data; title: Part C - Applications; title: ype-2 Fuzzy Logic in Image Analysis and Pattern Recognition; title: Reliable Tool Life Estimation with Multiple Acoustic Emission Signal Feature Selection and Integration Based on Type-2 Fuzzy Logic; title: A Review of Cluster Validation with an Example of Type-2 Fuzzy Application in R; title: Type-2 Fuzzy Set and Fuzzy Ontology for Diet Application.