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Fuzzy regression model of goal difference of the Korean National Football Team based on ELO rating and dividend

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dc.contributor.authorLee, Woo-Joo-
dc.contributor.authorJhang, Hyo-Jin-
dc.contributor.authorChoi, Seung Hoe-
dc.date.accessioned2023-08-16T07:43:59Z-
dc.date.available2023-08-16T07:43:59Z-
dc.date.issued2020-04-
dc.identifier.issn1064-1246-
dc.identifier.issn1875-8967-
dc.identifier.urihttps://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114188-
dc.description.abstractSoccer recently has become an intellectual game by predicting the outcome of games. In this study, we use path analysis to find the variable that affects the outcome of the Korea National Football Team (KNFT) matches the most, and consequently the odds of victory, defeat, or a draw, as announced by the betting company. We will also investigate the influence of the variables inferred from the path analysis and Korea's ELO Rating on the difference between scoring and losing points of the KNFT. We will represent the dividend and the difference between scoring and losing points as fuzzy numbers using the fuzzy decomposition, and then infer the fuzzy regression model for the result of the KNFT's match. For this purpose, we use data on 113 games of the KNFT from September 2011 to June 2019 and the dividend rate of the KNFT obtained from Wise Toto company.-
dc.format.extent7-
dc.language영어-
dc.language.isoENG-
dc.publisherIOS Press-
dc.titleFuzzy regression model of goal difference of the Korean National Football Team based on ELO rating and dividend-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.3233/JIFS-191288-
dc.identifier.wosid000534641700086-
dc.identifier.bibliographicCitationJournal of Intelligent and Fuzzy Systems, v.38, no.4, pp 4537 - 4543-
dc.citation.titleJournal of Intelligent and Fuzzy Systems-
dc.citation.volume38-
dc.citation.number4-
dc.citation.startPage4537-
dc.citation.endPage4543-
dc.type.docType정기학술지(Article(Perspective Article포함))-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.subject.keywordPlusODDS-
dc.subject.keywordAuthorELO rating-
dc.subject.keywordAuthordividend-
dc.subject.keywordAuthorpath analysis-
dc.subject.keywordAuthorfuzzy partition-
dc.subject.keywordAuthorregression analysis-
dc.identifier.urlhttps://eds.s.ebscohost.com/eds/pdfviewer/pdfviewer?vid=1&sid=c685f7dc-79b9-4560-9d24-5bcefc6822f8%40redis-
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ERICA 과학기술융합대학 (ERICA 수리데이터사이언스학과)
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