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Advances in Type-2 Fuzzy Sets and Systems

Advances in Type-2 Fuzzy Sets and Systems Theory and Applications / [electronic resource] : edited by Alireza Sadeghian, Jerry M. Mendel, Hooman Tahayori. - X, 262 p. 103 illus., 41 illus. in color. online resource. - Studies in Fuzziness and Soft Computing, 301 1434-9922 ; . - Studies in Fuzziness and Soft Computing, 301 .

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.

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.


10.1007/978-1-4614-6666-6 doi

Artificial intelligence.
Computational intelligence.
Computational Intelligence.
Artificial Intelligence (incl. Robotics).