By Jerry Mendel, Dongrui Wu
Explains for the 1st time how "computing with phrases" can relief in making subjective judgmentsLotfi Zadeh, the daddy of fuzzy good judgment, coined the word "computing with phrases" (CWW) to explain a technique within which the gadgets of computation are phrases and propositions drawn from a traditional language. Perceptual Computing explains find out how to enforce CWW to help within the very important region of creating subjective judgments, utilizing a strategy that results in an interactive device—a "Perceptual Computer"—that propagates random and linguistic uncertainties into the subjective judgment in a manner that may be modeled and saw by means of the judgment maker.This publication makes a speciality of the 3 elements of a Perceptual Computer—encoder, CWW engines, and decoder—and then offers exact functions for every. It makes use of period type-2 fuzzy units (IT2 FSs) and fuzzy common sense because the mathematical car for perceptual computing, simply because such fuzzy units can version first-order linguistic uncertainties while the standard type of fuzzy units can't. Drawing upon the paintings on subjective judgments that Jerry Mendel and his scholars accomplished during the last decade, Perceptual Computing exhibits readers how to:Map word-data with its inherent uncertainties into an IT2 FS that captures those uncertaintiesUse uncertainty measures to quantify linguistic uncertaintiesCompare IT2 FSs through the use of similarity and rankCompute the subsethood of 1 IT2 FS in one other such setAggregate disparate facts, starting from numbers to uniformly weighted durations to nonuniformly weighted durations to wordsAggregate multiple-fired IF-THEN principles in order that the integrity of be aware IT2 FS types is preservedFree MATLAB-based software program is usually to be had on-line so readers can practice the method of perceptual computing instantly, or even attempt to increase upon it. Perceptual Computing is a crucial go-to for researchers and scholars within the fields of man-made intelligence and fuzzy good judgment, in addition to for operations researchers, choice makers, psychologists, laptop scientists, and computational intelligence specialists.
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Extra resources for Perceptual Computing: Aiding People in Making Subjective Judgments (IEEE Press Series on Computational Intelligence)
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Mendel, Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions, Upper-Saddle River, NJ: Prentice-Hall, 2001b. J. M. Mendel, “An architecture for making judgments using computing with words,” Int. J. Appl. Math. Comput. , vol. 12, No. 3, pp. 325–335, 2002. J. M. Mendel, “Type-2 fuzzy sets: some questions and answers,” IEEE Connections, Newsletter of the IEEE Neural Networks Society, vol. 1, pp. 10–13, 2003a. J. M. Mendel, “Fuzzy sets for words: a new beginning,” in Proceedings of FUZZ-IEEE 2003, St.
Consequently, in this book IT2 FSs are used to model words. 15 For example, if the CWW engine is a set of if–then rules (see Chapter 6), then choices must be made about: ț Shapes of MFs for each IT2 FS. 15 The material in this section is taken from Mendel (2007c). 20 INTRODUCTION ț Mathematical operators used to model the antecedent connector words and and or. , Klir and Yuan (1995)]. , Klir and Yuan (1995)]. , Klir and Yuan (1995)]. The result is an aggregated IT2 FS. , (Wu and Mendel (2008a)].
The input translator translates these descriptions into fuzzy numbers for input to a fuzzy expert system. The fuzzy expert system processes these fuzzy numbers into fuzzy number outputs describing suggestions to the human operators. The output translator, which is a neural net, takes the fuzzy number output from the fuzzy expert system, and produces verbal suggestions, of what to do, for the human operators. The translation of fuzzy numbers into words is called inverse linguistic approximation.