Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/76761
DC FieldValueLanguage
dc.contributor應數系-
dc.creatorWu, Berlin-
dc.creator吳柏林zh_TW
dc.creatorNguyen, H.T.en_US
dc.date2006-
dc.date.accessioned2015-07-21T07:29:30Z-
dc.date.available2015-07-21T07:29:30Z-
dc.date.issued2015-07-21T07:29:30Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/76761-
dc.description.abstractIn social science research, many decisions, evaluations, or purposes of evaluations are done by surveys or questionnaires to seek for people`s consensus. The commonly used method is asking people to think in binary logic way from a multiple choice design. However, these processes often ignore the fuzzy, sometimes even ambiguous thinking behavior perceived in human logic and recognition. © Springer-Verlag Berlin Heidelberg 2006.-
dc.format.extent176 bytes-
dc.format.mimetypetext/html-
dc.relationStudies in Fuzziness and Soft Computing, 198, 109-128-
dc.titleFuzzy statistical analysis and estimation-
dc.typearticleen
dc.identifier.doi10.1007/11353492_7-
dc.doi.urihttp://dx.doi.org/10.1007/11353492_7-
item.grantfulltextrestricted-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypearticle-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
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