Modeling of fuzzy data

Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/76757

DC Field	Value	Language
dc.contributor	應數系	-
dc.creator	Wu, Berlin	-
dc.creator	吳柏林	zh_TW
dc.creator	Nguyen, H.T	en_US
dc.date	2006	-
dc.date.accessioned	2015-07-21T07:29:22Z	-
dc.date.available	2015-07-21T07:29:22Z	-
dc.date.issued	2015-07-21T07:29:22Z	-
dc.identifier.uri	http://nccur.lib.nccu.edu.tw/handle/140.119/76757	-
dc.description.abstract	Fuzzy data are imprecise data obtained from measurements, perception or by interviewing people. Typically, those data are expressed in linguistic terms (in qualitative form). For example, \"Tony is young\", is a useful information, and yet it is not quite clear how we could model it mathematically for processing. The adjective young is intended to give an elastic constraint on the unobservable variable X (age of Tony), the range of X is [0, 100], say. © Springer-Verlag Berlin Heidelberg 2006.	-
dc.format.extent	176 bytes	-
dc.format.mimetype	text/html	-
dc.relation	Studies in Fuzziness and Soft Computing, 198, 13-34	-
dc.title	Modeling of fuzzy data	-
dc.type	article	en
dc.identifier.doi	10.1007/11353492_3	-
dc.doi.uri	http://dx.doi.org/10.1007/11353492_3	-
item.cerifentitytype	Publications	-
item.openairecristype	http://purl.org/coar/resource_type/c_18cf	-
item.grantfulltext	restricted	-
item.openairetype	article	-
item.fulltext	With Fulltext	-
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