Titlebook: Mathematics of Fuzziness—Basic Issues; Xuzhu Wang,Da Ruan,Etienne E. Kerre Book 2009 Springer-Verlag Berlin Heidelberg 2009 AI.Algebra.Com

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Basics of Fuzzy Sets,ecomposition of a fuzzy set, and mathematical representations of fuzzy sets in terms of a nest of sets. Towards the end of the chapter, fuzzy sets taking values in [0,1] are extended to those on a lattice and a similar investigation is carried out.

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Mathematics of Fuzziness—Basic Issues978-3-540-78311-4Series ISSN 1434-9922 Series E-ISSN 1860-0808

Eructation

el-based predictive control paradigm. This text by R. Ansari and M. Tade gives an excellent synthesis of this new direction. Two strengths emphasized by the text are: (i) four applications found in refinery processes are used to give the text a firm practical continuity; (ii) a non-linear model-base

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Xuzhu Wang,Da Ruan,Etienne E. Kerreegression models. The features “l(fā)ocal minima” and “ill-conditioning” are discussed and interpreted in the common framework. It is shown that a local minimum in a neural network model has close relations to the case where one has a poor choice of basis function in a traditional model. Further, it is

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雇傭兵

Extension Principle and Fuzzy Numbers,tional mathematical theory can give little help as to make a decision with such kind of imperfect knowledge. On the contrast, fuzzy set theory provides a strongly effective apparatus to deal with the problem. Firstly, imprecise descriptions can be modeled by means of fuzzy numbers. That is to say, t