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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Vladik Kreinovich | en_US |
| dc.contributor.author | Hung T. Nguyen | en_US |
| dc.contributor.author | Olga Kosheleva | en_US |
| dc.contributor.author | Rujira Ouncharoen | en_US |
| dc.date.accessioned | 2018-09-04T10:13:15Z | - |
| dc.date.available | 2018-09-04T10:13:15Z | - |
| dc.date.issued | 2015-01-01 | en_US |
| dc.identifier.issn | 18758967 | en_US |
| dc.identifier.issn | 10641246 | en_US |
| dc.identifier.other | 2-s2.0-84944589539 | en_US |
| dc.identifier.other | 10.3233/IFS-151723 | en_US |
| dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84944589539&origin=inward | en_US |
| dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/54423 | - |
| dc.description.abstract | © 2015 - IOS Press and the authors. While many objects and processes in the real world are discrete, from the computational viewpoint, discrete objects and processes are much more difficult to handle than continuous ones. As a result, a continuous approximation is often a useful way to describe discrete objects and processes.We show that the need for such an approximation explains many features of fuzzy techniques, and we speculate on to which promising future directions of fuzzy research this need can lead us. | en_US |
| dc.subject | Computer Science | en_US |
| dc.subject | Engineering | en_US |
| dc.subject | Mathematics | en_US |
| dc.title | 50 Years of fuzzy: From discrete to continuous to - Where? | en_US |
| dc.type | Journal | en_US |
| article.title.sourcetitle | Journal of Intelligent and Fuzzy Systems | en_US |
| article.volume | 29 | en_US |
| article.stream.affiliations | University of Texas at El Paso | en_US |
| article.stream.affiliations | New Mexico State University Las Cruces | en_US |
| article.stream.affiliations | Chiang Mai University | en_US |
| Appears in Collections: | CMUL: Journal Articles | |
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