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DC Field | Value | Language |
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dc.contributor.author | Roengchai Tansuchat | en_US |
dc.contributor.author | Uyen Pham | en_US |
dc.contributor.author | Chon Van Le | en_US |
dc.date.accessioned | 2020-10-14T08:31:17Z | - |
dc.date.available | 2020-10-14T08:31:17Z | - |
dc.date.issued | 2020-01-01 | en_US |
dc.identifier.issn | 14337479 | en_US |
dc.identifier.issn | 14327643 | en_US |
dc.identifier.other | 2-s2.0-85087785182 | en_US |
dc.identifier.other | 10.1007/s00500-020-05154-6 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85087785182&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/70459 | - |
dc.description.abstract | © 2020, Springer-Verlag GmbH Germany, part of Springer Nature. Several typical econometric analyses, namely fuzzy coalitional games, regression for causal inference, statistical quality control, and prediction in machine learning, are examined in this paper to point out that soft computing components such as fuzzy theory and random set theory have a major role to play. The examination of these statistical analyses suggests an extended use of random fuzzy sets, based upon theory of random fuzzy sets, to improve empirical research. | en_US |
dc.subject | Computer Science | en_US |
dc.subject | Mathematics | en_US |
dc.title | On soft computing with random fuzzy sets in econometrics and machine learning | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Soft Computing | en_US |
article.stream.affiliations | University of Economics Ho Chi Minh City | en_US |
article.stream.affiliations | International University,Vietnam National University Ho Chi Minh City | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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