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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Andrzej Pownuk | en_US |
dc.contributor.author | Vladik Kreinovich | en_US |
dc.contributor.author | Songsak Sriboonchitta | en_US |
dc.date.accessioned | 2018-09-05T04:26:35Z | - |
dc.date.available | 2018-09-05T04:26:35Z | - |
dc.date.issued | 2018-01-01 | en_US |
dc.identifier.issn | 21984190 | en_US |
dc.identifier.issn | 21984182 | en_US |
dc.identifier.other | 2-s2.0-85032701170 | en_US |
dc.identifier.other | 10.1007/978-3-319-69989-9_14 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85032701170&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/58593 | - |
dc.description.abstract | © 2018, Springer International Publishing AG. Usual algorithms for fuzzy data processing—based on the usual form of Zadeh’s extension principle—implicitly assume that we use the min “and”-operation (t-norm). It is known, however, that in many practical situations, other t-norms more adequately describe human reasoning. It is therefore desirable to extend the usual algorithms to situations when we use t-norms different from min. Such an extension is provided in this chapter. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Decision Sciences | en_US |
dc.subject | Economics, Econometrics and Finance | en_US |
dc.subject | Engineering | en_US |
dc.subject | Mathematics | en_US |
dc.subject | Social Sciences | en_US |
dc.title | Fuzzy data processing beyond min t-norm | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Systems, Decision and Control | en_US |
article.volume | 125 | en_US |
article.stream.affiliations | University of Texas at El Paso | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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