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Titlebook: An Introduction to Fuzzy Logic Applications in Intelligent Systems; Ronald R. Yager,Lotfi A. Zadeh Book 1992 Springer Science+Business Med

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Fuzzy Sets in Natural Language Processing, human way of thinking and regarding the world. Therefore, it is extremely important to study it in all its respects. Much has been done in understanding its structure, especially the phonetic and syntactic aspects. Less, however, is understood its semantics. There are many linguistic systems, often
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Fuzzy-Set-Theoretic Applications in Modeling of Man-Machine Interactions,rwise be possible to be made; and 2) epistemiological, to express and extend our knowledge of the world. Models are helpful for explanation and theory formation, as well as simplication and concretization. Zimmermann (1980) classifies models into three groups: 1) formal models (purely axiomatic syst
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Fuzzy Logic Knowledge Systems and Artificial Neural Networks in Medicine and Biology,amework of medical diagnosis problems. The paper describes and illustrates with practical examples, a general methodology of special interest in the processing of borderline cases, that allows a graded assignment of diagnoses to patients. A pattern of medical knowledge consists of a tableau with lin
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The Representation and Use of Uncertainty and Metaknowledge in Milord,em in programs. Experts in a domain are better than novices in performing problem solving tasks. This is due to their greater experience in solving problems that provides them with better strategies. Such strategies are knowledge about how to use the knowledge they have in their domain of expertise.
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Probabilistic Sets Probabilistic Extension of Fuzzy Sets,)variety of character, (3)subjectivity of observers, (4)evolution of knowledge or learning. With regard to each problem, however, there are several general theories: many-valued logic, fuzzy set theory (in connection with (1)and(2)), modal logic (in conjunction with (2)and(4)), and subjective probab
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