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Linguistic Fuzzy Logic Methods in Social Sciences


Menge:  Stück  
Produktinformationen
cover
cover
Artikel-Nr.:
     5667A-9783642422379
Hersteller:
     Springer Verlag
Herst.-Nr.:
     9783642422379
EAN/GTIN:
     9783642422379
Suchbegriffe:
Maschinenbau und Fertigungstechnik
Maschinenbau und Fertigungstechnik ...
allgemeine Technikbücher
allgemeine Technikbücher - englisch...
The modern origin of fuzzy sets, fuzzy algebra, fuzzy decision making, and "computing with words" is conventionally traced to Lotfi Zadeh's publication in 1965 of his path-breaking refutation of binary set theory. In a sixteen-page article, modestly titled "Fuzzy Sets" and published in the journal Information and Control, Zadeh launched a multi-disciplinary revolution. The start was relatively slow, but momentum gathered quickly. From 1970 to 1979 there were about 500 journal publications with the word fuzzy in the title; from 2000 to 2009 there were more than 35,000. At present, citations to Zadeh's publications are running at a rate of about 1,500-2,000 per year, and this rate continues to rise. Almost all applications of Zadeh's ideas have been in highly technical scientific fields, not in the social sciences. Zadeh was surprised by this development. In a personal note he states: "When I wrote my l965 paper, I expected that fuzzy set theory would be applied primarily in the realm of human sciences. Contrary to my expectation, fuzzy set theory and fuzzy logic are applied in the main in physical and engineering sciences." In fact, the first comprehensive examination of fuzzy sets by a social scientist did not appear until 1987, a full twenty-two years after the publication of Zadeh's seminal article, when Michael Smithson, an Australian psychologist, published Fuzzy Set Analysis for Behavioral and Social Sciences.
Weitere Informationen:
Author:
Badredine Arfi
Verlag:
Springer Berlin
Sprache:
eng
Weitere Suchbegriffe: maschinenbau und fertigungstechnik, Fuzziness; Linguistic Fuzzy Logic Methods; Type-2 Fuzzy Sets; fuzzy; fuzzy logic; logic, Linguistic Fuzzy Logic Methods, Type-2 Fuzzy Sets, fuzziness, fuzzy, fuzzy logic, logic
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