Jerry Mendel, Dongrui Wu

Perceptual Computing

• Broschiertes Buch

Produktbeschreibung

Lotfi Zadeh, the father of fuzzy logic, coined the phrase computing with words (CWW) to describe a methodology in which the computation objects are words drawn from a natural language. This text explains how to implement CWW for making subjective judgments using the three components of a Perceptual Computer (encoder, CWW engines, and decoder) and then providing detailed applications. The coverage divides the content into application chapters and detail chapters, including brief summaries of detail chapters for readers more interested in applications. This is an important go-to for researchers and students in AI, fuzzy logic, computer science in general, and psychology.

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Explains for the first time how "computing with words" can aid in making subjective judgments

Lotfi Zadeh, the father of fuzzy logic, coined the phrase "computing with words" (CWW) to describe a methodology in which the objects of computation are words and propositions drawn from a natural language. Perceptual Computing explains how to implement CWW to aid in the important area of making subjective judgments, using a methodology that leads to an interactive device--a "Perceptual Computer"--that propagates random and linguistic uncertainties into the subjective judgment in a way that can be modeled and observed by the judgment maker.

This book focuses on the three components of a Perceptual Computer--encoder, CWW engines, and decoder--and then provides detailed applications for each. It uses interval type-2 fuzzy sets (IT2 FSs) and fuzzy logic as the mathematical vehicle for perceptual computing, because such fuzzy sets can model first-order linguistic uncertainties whereas the usual kind of fuzzy sets cannot. Drawing upon the work on subjective judgments that Jerry Mendel and his students completed over the past decade, Perceptual Computing shows readers how to:
Map word-data with its inherent uncertainties into an IT2 FS that captures these uncertainties
Use uncertainty measures to quantify linguistic uncertainties
Compare IT2 FSs by using similarity and rank
Compute the subsethood of one IT2 FS in another such set
Aggregate disparate data, ranging from numbers to uniformly weighted intervals to nonuniformly weighted intervals to words
Aggregate multiple-fired IF-THEN rules so that the integrity of word IT2 FS models is preserved

Free MATLAB-based software is also available online so readers can apply the methodology of perceptual computing immediately, and even try to improve upon it. Perceptual Computing is an important go-to for researchers and students in the fields of artificial intelligence and fuzzy logic, as well as for operations researchers, decision makers, psychologists, computer scientists, and computational intelligence experts.

Produktdetails

• IEEE Press Series on Computational Intelligence
• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 336
• Erscheinungstermin: 26. April 2010
• Englisch
• Abmessung: 234mm x 156mm x 18mm
• Gewicht: 515g
• ISBN-13: 9780470478769
• ISBN-10: 0470478764
• Artikelnr.: 28242077

Autorenporträt

Jerry M. Mendel is Professor of Electrical Engineering at the University of Southern California. A Life Fellow of the IEEE and a Distinguished Member of the IEEE Control Systems Society, Mendel is also the recipient of many awards for his diverse research, including the IEEE Centennial Medal, the Fuzzy Systems Pioneer Award from the IEEE Computational Intelligence Society, and the IEEE Third Millennium Medal. Dongrui Wu is a Postdoctoral Research Associate at the University of Southern California, where he recently obtained his PhD in electrical engineering.

Inhaltsangabe

Preface. 1 Introduction. 1.1 Perceptual Computing. 1.2 Examples. 1.3
Historical Origins of Perceptual Computing. 1.4 How to Validate the
Perceptual Computer. 1.5 The Choice of Fuzzy Set Models for the Per-C. 1.6
Keeping the Per-C as Simple as Possible. 1.7 Coverage of the Book. 1.8
High-Level Synopses of Technical Details. References. 2 Interval Type-2
Fuzzy Sets. 2.1 A Brief Review of Type-1 Fuzzy Sets. 2.2 Introduction to
Interval Type-2 Fuzzy Sets. 2.3 Definitions. 2.4 Wavy-Slice Representation
Theorem. 2.5 Set-Theoretic Operations. 2.6 Centroid of an IT2 FS. 2.7 KM
Algorithms. 2.8 Cardinality and Average Cardinality of an IT2 FS. 2.9 Final
Remark. Appendix 2A. Derivation of the Union of Two IT2 FSs. Appendix 2B.
Enhanced KM (EKM) Algorithms. References. 3 Encoding: From a Word to a
Model--The Codebook. 3.1 Introduction. 3.2 Person FOU Approach for a Group
of Subjects. 3.3 Collecting Interval End-Point Data. 3.4 Interval
End-Points Approach. 3.5 Interval Approach. 3.6 Hedges. Appendix 3A.
Methods for Eliciting T1 MF Information From Subjects. Appendix 3B.
Derivation of Reasonable Interval Test. References. 4 Decoding: From FOUs
to a Recommendation. 4.1 Introduction. 4.2 Similarity Measure Used as a
Decoder. 4.3 Ranking Method Used as a Decoder. 4.4 Classifier Used as a
Decoder. 5 Novel Weighted Averages as a CWW Engine. 5.1 Introduction. 5.2
Novel Weighted Averages. 5.3 Interval Weighted Average. 5.4 Fuzzy Weighted
Average. 5.5 Linguistic Weighted Average. 5.6 A Special Case of the LWA.
5.7 Fuzzy Extensions of Ordered Weighted Averages. 6 IF-THEN Rules as a CWW
Engine--Perceptual Reasoning. 6.1 Introduction. 6.2 A Brief Overview of
Interval Type-2 Fuzzy Logic Systems. 6.3 Perceptual Reasoning:
Computations. 6.4 Perceptual Reasoning: Properties. 7 Assisting in Making
Investment Choices--Investment Judgment Advisor (IJA). 7.1 Introduction.
7.2 Encoder for the IJA. 7.3 Reduction of the Codebooks to User-Friendly
Codebooks. 7.4 CWW Engine for the IJA. 7.5 Decoder for the IJA. 7.6
Examples. 7.7 Interactive Software for the IJA. 7.8 Conclusions.
References. 8 Assisting in Making Social Judgments--Social Judgment Advisor
(SJA). 8.1 Introduction. 8.2 Design an SJA. 8.3 Using an SJA. 8.4
Discussion. 8.5 Conclusions. References. 9 Assisting in Hierarchical
Decision Making--Procurement Judgment Advisor (PJA). 9.1 Introduction. 9.2
Missile Evaluation Problem Statement. 9.3 Per-C for Missile Evaluation:
Design. 9.4 Per-C for Missile Evaluation: Examples. 9.5 Comparison with
Previous Approaches. 9.6 Conclusions. Appendix 9A: Some Hierarchical
Multicriteria Decision-Making Applications. References. 10 Assisting in
Hierarchical and Distributed Decision Making-- Journal Publication Judgment
Advisor (JPJA)/ 10.1 Introduction. 10.2 The Journal Publication Judgment
Advisor (JPJA). 10.3 Per-C for the JPJA. 10.4 Examples. 10.4.5 Complete
Reviews. 10.5 Conclusions. Reference. 11 Conclusions. 11.1 Perceptual
Computing Methodology. 11.2 Proposed Guidelines for Calling Something CWW.
Index.