Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/48302
DC FieldValueLanguage
dc.creator吳柏林zh_TW
dc.date1999-
dc.date.accessioned2010-11-12T04:16:47Z-
dc.date.available2010-11-12T04:16:47Z-
dc.date.issued2010-11-12T04:16:47Z-
dc.identifier.urihttp://nccur.lib.nccu.edu.tw/handle/140.119/48302-
dc.description.abstractMany applications of probability theory are based on the assumption that, as the number of cases increase, the relative frequency of cases with a certain property tends to a number – probability that this property is true. L. Zadeh has shown that in many real-life situations, the frequency oscillates and does not converge at all. It is very difficult to describe such situations by using methods from traditional probability theory. Fuzzy logic is not based on any convergence assumptions and therefore, provides a natural description of such situations. However, a natural next question arises: how can we describe this oscillating behavior? Since we cannot describe it by using a single parameter (such as probability), we need to use a multi-D formalism. In this paper, we describe an optimal formalism for describing such oscillations, and show that it complements traditional probability techniques in the same way as fractals complement smooth curves and surfaces.-
dc.languagezh_TWen
dc.language.isoen_US-
dc.relationInternational Journal of Uncertainty Fuzziness and Knowledge - Based Systems,7(4),363-370en
dc.subjectMulti-D degrees of belief; fractal; fuzzy; probability-
dc.titleFuzzy/Probability~Fractal/Smoothen
dc.typearticleen
dc.identifier.doi10.1142/S0218488599000313-
dc.doi.urihttp://dx.doi.org/10.1142/S0218488599000313-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.openairetypearticle-
item.languageiso639-1en_US-
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