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Fuzzy control as a fuzzy deduction system
Fuzzy Sets and Systems, 2001The author gives a new and interesting translation strategy for linguistic control rules of the form: \textit{if} \(x\) is \(A\) \textit{then} \(y\) is \(B\). He reads them as: \( A(x) \land B(y) \to\text{ good} (x,y) \) with a new predicate \textit{good} expressing globally the control quality.
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Fuzzy Preorder, Fuzzy Topology and Fuzzy Transition System
2013The purpose of this work is to show that the observations made regarding fuzzy transition systems can be easily obtained by using the fuzzy preordered and fuzzy topological concepts.
S. P. Tiwari, Anupam K. Singh
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Kybernetes, 1990
The concept of L‐fuzzy systems is introduced as a generalisation of that of general systems. A universal structure of a special kind of L‐fuzzy system is given, some mapping properties of L‐fuzzy systems are studied and a number of open questions posed.
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The concept of L‐fuzzy systems is introduced as a generalisation of that of general systems. A universal structure of a special kind of L‐fuzzy system is given, some mapping properties of L‐fuzzy systems are studied and a number of open questions posed.
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Kybernetes, 1988
With the object of translating some concepts and results from classical Reliability Theory into particular types of multistate systems, this article starts by presenting some basic definitions of fuzzy systems. The concepts of fuzzy coherent and fuzzy crisp‐based systems are examined and some results on fuzzy coherent structures are presented.
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With the object of translating some concepts and results from classical Reliability Theory into particular types of multistate systems, this article starts by presenting some basic definitions of fuzzy systems. The concepts of fuzzy coherent and fuzzy crisp‐based systems are examined and some results on fuzzy coherent structures are presented.
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European Journal of Operational Research, 2004
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International Journal of General Systems, 1990
The notion of fuzziness as defined in this paper relates to situations in which the source of imprecision is not a random variable or a stochastic process, but rather a class or classes which do not possess sharply defined boundaries, e.g., the “class of bald men,” or the “class of numbers which are much greater than 10,” or the “class of adaptive ...
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The notion of fuzziness as defined in this paper relates to situations in which the source of imprecision is not a random variable or a stochastic process, but rather a class or classes which do not possess sharply defined boundaries, e.g., the “class of bald men,” or the “class of numbers which are much greater than 10,” or the “class of adaptive ...
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Ukrainian Mathematical Journal, 2018
The asymptotic methods aimed at the investigation of nonlinear differential equations occupy a central place in the nonlinear mechanics. Krylov and Bogolyubov were the first who developed a general algorithm and proved the theorem on closeness of the solutions of exact and averaged systems.
Perestyuk, N. A., Skripnik, N. V.
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The asymptotic methods aimed at the investigation of nonlinear differential equations occupy a central place in the nonlinear mechanics. Krylov and Bogolyubov were the first who developed a general algorithm and proved the theorem on closeness of the solutions of exact and averaged systems.
Perestyuk, N. A., Skripnik, N. V.
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Identification in fuzzy systems
IEEE Transactions on Systems, Man, and Cybernetics, 1984Given are fuzzy relational equations of the type \(Y=X\circ R\), \(Y=X*R\), \(Y=X\square R\), where X,Y denote fuzzy sets of input and output, R a fuzzy relation, and \(\circ\), *, \(\square\) are sup-min, sup-prod, inf-max composition operators, respectively. This paper deals with identification methods in fuzzy systems.
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1994
The aim of this paper is to study fuzzy dynamic systems. The role of fuzzy sets in formation of a conceptual and computational platform for symbolic and numerical information processing is identified. We summarize essential properties of fuzzy partitions developed with the aid of families of fuzzy sets.
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The aim of this paper is to study fuzzy dynamic systems. The role of fuzzy sets in formation of a conceptual and computational platform for symbolic and numerical information processing is identified. We summarize essential properties of fuzzy partitions developed with the aid of families of fuzzy sets.
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Fuzzy-Systeme und Neuro-Fuzzy-Systeme
1998Die Anwendung von Fuzzy-Systemen hat sich in den letzten Jahren immer mehr in Bereiche der Betriebswirtschaft, Datenanalyse, Medizin usw. erstreckt und ist keineswegs mehr auf technische Anwendungen beschrankt. Gleichzeitig spielen Kopplungen von Fuzzy-Systemen mit anderen Methoden des Soft Computing eine immer grosere Rolle.
Detlef Nauck, Rudolf Kruse
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