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dc.contributor.authorYu, Jing-Rungen_US
dc.contributor.authorTzeng, Gwo-Hshiungen_US
dc.date.accessioned2014-12-08T15:09:24Z-
dc.date.available2014-12-08T15:09:24Z-
dc.date.issued2009-06-01en_US
dc.identifier.issn0218-4885en_US
dc.identifier.urihttp://dx.doi.org/10.1142/S0218488509005929en_US
dc.identifier.urihttp://hdl.handle.net/11536/7176-
dc.description.abstractThis study proposes fuzzy multiple objective programming to determine the measure of fitness and the number of change-points in an interval piecewise regression model. To increase the measure of fitness, Tanaka and Lee proposed a conceptual procedure, which is a heuristic approach and becomes complicated for determining the proper polynomial. Therefore, a multiple objective approach is adopted to obtain a compromise solution among three objectives - maximizing the measure of fitness, minimizing the number of change-points and minimizing the width to obtain the interval regression models. By using the proposed method, a better measure of fitness can be obtained. Two numerical examples are used as demonstrations to illustrate our approach in more detail.en_US
dc.language.isoen_USen_US
dc.subjectInterval regressionen_US
dc.subjectpiecewise regressionen_US
dc.subjectchange-pointen_US
dc.subjectquadratic programmingen_US
dc.subjectfuzzy multiple objective programmingen_US
dc.titleFUZZY MULTIPLE OBJECTIVE PROGRAMMING IN AN INTERVAL PIECEWISE REGRESSION MODELen_US
dc.typeArticleen_US
dc.identifier.doi10.1142/S0218488509005929en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMSen_US
dc.citation.volume17en_US
dc.citation.issue3en_US
dc.citation.spage365en_US
dc.citation.epage376en_US
dc.contributor.department科技管理研究所zh_TW
dc.contributor.departmentInstitute of Management of Technologyen_US
dc.identifier.wosnumberWOS:000266771100005-
dc.citation.woscount3-
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