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dc.contributor.authorChen, SMen_US
dc.contributor.authorHwang, JRen_US
dc.date.accessioned2014-12-08T15:45:27Z-
dc.date.available2014-12-08T15:45:27Z-
dc.date.issued2000-04-01en_US
dc.identifier.issn1083-4419en_US
dc.identifier.urihttp://dx.doi.org/10.1109/3477.836375en_US
dc.identifier.urihttp://hdl.handle.net/11536/30610-
dc.description.abstractA drawback of traditional forecasting methods is that they can not deal with forecasting problems in which the historical data are represented by linguistic values. Using fuzzy time series to deal with forecasting problems can overcome this drawback. In this paper, we propose a new fuzzy time series model called the two-factors time-variant fuzzy time series model to deal with forecasting problems. Based on the proposed model,,ve develop two algorithms for temperature prediction. Both algorithms have the advantage of obtaining good forecasting results.en_US
dc.language.isoen_USen_US
dc.subjectmain-factor fuzzy time seriesen_US
dc.subjectsecond-factor fuzzy time seriesen_US
dc.subjecttemperature predictionen_US
dc.subjecttime-invariant fuzzy time seriesen_US
dc.subjecttime-variant fuzzy time seriesen_US
dc.titleTemperature prediction using fuzzy time seriesen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/3477.836375en_US
dc.identifier.journalIEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICSen_US
dc.citation.volume30en_US
dc.citation.issue2en_US
dc.citation.spage263en_US
dc.citation.epage275en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000086532400002-
dc.citation.woscount144-
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