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Titlebook: Axiomatic Fuzzy Set Theory and Its Applications; Xiaodong Liu,Witold Pedrycz Book 2009 Springer-Verlag Berlin Heidelberg 2009 AFS Theory.A

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发表于 2025-3-21 19:09:07 | 显示全部楼层 |阅读模式
期刊全称Axiomatic Fuzzy Set Theory and Its Applications
影响因子2023Xiaodong Liu,Witold Pedrycz
视频video
发行地址First comprehensive, authoritative and up-to-date publication on Axiomatic Fuzzy Set theory.Covers detailed mathematical proofs and algorithms
学科分类Studies in Fuzziness and Soft Computing
图书封面Titlebook: Axiomatic Fuzzy Set Theory and Its Applications;  Xiaodong Liu,Witold Pedrycz Book 2009 Springer-Verlag Berlin Heidelberg 2009 AFS Theory.A
影响因子It is well known that “fuzziness”—informationgranulesand fuzzy sets as one of its formal manifestations— is one of important characteristics of human cognitionandcomprehensionofreality. Fuzzy phenomena existinnature and are encountered quite vividly within human society. The notion of a fuzzy set has been introduced by L. A. , Zadeh in 1965 in order to formalize human concepts, in connection with the representation of human natural language and computing with words. Fuzzy sets and fuzzy logic are used for mod- ing imprecise modes of reasoning that play a pivotal role in the remarkable human abilities to make rational decisions in an environment a?ected by - certainty and imprecision. A growing number of applications of fuzzy sets originated from the “empirical-semantic” approach. From this perspective, we were focused on some practical interpretations of fuzzy sets rather than being oriented towards investigations of the underlying mathematical str- tures of fuzzy sets themselves. For instance, in the context of control theory where fuzzy sets have played an interesting and practically relevant function, the practical facet of fuzzy sets has been stressed quite signi?cantly. Howeve
Pindex Book 2009
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发表于 2025-3-21 20:49:58 | 显示全部楼层
Latticestails, the readers may refer to [1, 3, 2]. Our purpose is to familiarize the readers with the concepts and fundamental results, which will be exploited in further discussion. Some results listed without proofs is left to the reader.
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AFS Logic, AFS Structure and Coherence Membership Functionsy logic for the AFS structure are proposed and a new framework of determining coherence membership functions is developed by taking both fuzziness (subjective imprecision) and randomness (objective uncertainty) into account. Singpurwalla’s measure of the fuzzy events in a probability space has been
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AFS Topology and Its Applicationsas, and elaborate on the main relations between these topological structures. Second, we apply the topology derived by a family of fuzzy concepts in ., where . is a set of simple concepts, to analyze the relations among the fuzzy concepts. Thirdly, we propose the differential degrees and fuzzy simil
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AFS Formal Concept and AFS Fuzzy Formal Concept Analysismatical treatment of fuzzy formal concept analysis referred to as an AFS Formal Concept Analysis (AFSFCA). It naturally augments the existing formal concepts to fuzzy formal concepts, with the aim of deriving their mathematical properties and applying them in the exploration and development of knowl
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AFS Fuzzy Clustering Analysis by taking advantage of the semantics captured by the AFS logic. Within the framework of AFS theory, we develop new techniques of feature selection, concept categorization and characteristic description (i.e.,the characteristic description of an object or a group of objects using the fuzzy concepts)
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AFS Fuzzy Classifierssion trees. The advantage of these classifiers is two-fold. First, they can mimic the human reasoning and in this manner offer a far more transparent and comprehensible way supporting the design of the classifiers. An important aspect is concerned with the simplicity of the design methodology and th
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