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research-article

Fuzzy logic = computing with words

Published: 01 May 1996 Publication History

Abstract

As its name suggests, computing with words (CW) is a methodology in which words are used in place of numbers for computing and reasoning. The point of this note is that fuzzy logic plays a pivotal role in CW and vice-versa. Thus, as an approximation, fuzzy logic may be equated to CW. There are two major imperatives for computing with words. First, computing with words is a necessity when the available information is too imprecise to justify the use of numbers, and second, when there is a tolerance for imprecision which can be exploited to achieve tractability, robustness, low solution cost, and better rapport with reality. Exploitation of the tolerance for imprecision is an issue of central importance in CW. In CW, a word is viewed as a label of a granule; that is, a fuzzy set of points drawn together by similarity, with the fuzzy set playing the role of a fuzzy constraint on a variable. The premises are assumed to be expressed as propositions in a natural language. In coming years, computing with words is likely to evolve into a basic methodology in its own right with wide-ranging ramifications on both basic and applied levels

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  • (2024)Credibility of a Membership Function Related to a Linguistic Value to Improve Computing With WordsIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.337470432:6(3458-3470)Online publication date: 12-Mar-2024
  • (2024)Fuzzy Feedback Multiagent Reinforcement Learning for Adversarial Dynamic Multiteam CompetitionsIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.336305332:5(2811-2824)Online publication date: 7-Feb-2024
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cover image IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems  Volume 4, Issue 2
May 1996
122 pages

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IEEE Press

Publication History

Published: 01 May 1996

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  • (2024)A Minimum Cost Consensus Model With Linguistic Information in an Asymmetric Costs Context to Prevent Manipulative Behavior for Emergency Decision MakingIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.339012332:7(4148-4162)Online publication date: 1-Jul-2024
  • (2024)Credibility of a Membership Function Related to a Linguistic Value to Improve Computing With WordsIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.337470432:6(3458-3470)Online publication date: 12-Mar-2024
  • (2024)Fuzzy Feedback Multiagent Reinforcement Learning for Adversarial Dynamic Multiteam CompetitionsIEEE Transactions on Fuzzy Systems10.1109/TFUZZ.2024.336305332:5(2811-2824)Online publication date: 7-Feb-2024
  • (2024)Medical decision support in the light of interactive granular computingInternational Journal of Approximate Reasoning10.1016/j.ijar.2023.109103165:COnline publication date: 1-Feb-2024
  • (2024)Towards the definition of spatial granulesFuzzy Sets and Systems10.1016/j.fss.2024.109027490:COnline publication date: 15-Aug-2024
  • (2024)A data-driven implicit deep adaptive neuro-fuzzy inference system capable of manifold learning for function approximationApplied Soft Computing10.1016/j.asoc.2024.111458155:COnline publication date: 1-Apr-2024
  • (2024)Medical diagnosis using interval type-2 fuzzy similarity measuresCluster Computing10.1007/s10586-024-04485-527:8(10455-10466)Online publication date: 1-Nov-2024
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  • (2024)Determining the model for short-term load forecasting using fuzzy logic and ANFISSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-024-09882-x28:19(11457-11470)Online publication date: 1-Oct-2024
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