Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/61559
DC FieldValueLanguage
dc.contributor應數系en_US
dc.creator吳柏林zh_TW
dc.creatorWu,Berlin-
dc.creatorHsu,Hui-Lien_US
dc.date2010.03en_US
dc.date.accessioned2013-11-11T01:39:24Z-
dc.date.available2013-11-11T01:39:24Z-
dc.date.issued2013-11-11T01:39:24Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/61559-
dc.description.abstractWe usually use the correlation coefficient to observe the relation of two variables. But if the data are exhibited by a fuzzy type, such as interval data, instead of the real number data, the traditional methods for evaluating correlation coefficients do not work. In this paper, we propose an innovative approach to measure the correlation for variables when the data are in the form of intervals. Such the correlation coefficient interval will be called the fuzzy correlation coefficient. Finally two empirical studies are given to compare the traditional correlation coefficient and the fuzzy correlation coefficient. The results show that the fuzzy correlation coefficient can provides an efficient and creative measurement in the perception measurement.en_US
dc.format.extent36962 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen_US-
dc.relationInternational Journal of Innovative Computing, Information and Control, 6(3) , 1049-1058en_US
dc.subjectFuzzy correlation coefficient ; Interval data ; Fuzzy statisticsen_US
dc.titleAn Innovative Approach on Fuzzy Correlation Coefficient with Interval Dataen_US
dc.typearticleen
item.languageiso639-1en_US-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.openairetypearticle-
item.grantfulltextopen-
item.cerifentitytypePublications-
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