Our Reasoning is Clearly Fuzzy, So Why Is Crisp Logic So Often Adequate?

Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/80601

DC Field	Value	Language
dc.contributor	應數系	-
dc.creator	Wu, Berlin	-
dc.creator	吳柏林	zh_TW
dc.creator	Kreinovich, Vladik	en_US
dc.creator	Nguyen, Hung T.	en_US
dc.date	2015-06	-
dc.date.accessioned	2016-01-15T06:23:04Z	-
dc.date.available	2016-01-15T06:23:04Z	-
dc.date.issued	2016-01-15T06:23:04Z	-
dc.identifier.uri	http://nccur.lib.nccu.edu.tw/handle/140.119/80601	-
dc.description.abstract	Our reasoning is clearly fuzzy, so why is crisp logic so often adequate? We explain this phenomenon by showing that in the presence of noise, an arbitrary continuous (e.g., fuzzy) system can be well described by its discrete analog. However, as the description gets more accurate, the continuous description becomes necessary.	-
dc.format.extent	235015 bytes	-
dc.format.mimetype	application/pdf	-
dc.relation	International Journal of Intelligent Technologies & Applied Statistics, 8(2), 133-137	-
dc.title	Our Reasoning is Clearly Fuzzy, So Why Is Crisp Logic So Often Adequate?	-
dc.type	article	-
dc.identifier.doi	10.6148/IJITAS.2015.0802.05	-
dc.doi.uri	http://dx.doi.org/10.6148/IJITAS.2015.0802.05	-
item.grantfulltext	restricted	-
item.openairetype	article	-
item.openairecristype	http://purl.org/coar/resource_type/c_18cf	-
item.cerifentitytype	Publications	-
item.fulltext	With Fulltext	-
Appears in Collections:	期刊論文

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