Topic
Fuzzy number
About: Fuzzy number is a research topic. Over the lifetime, 35606 publications have been published within this topic receiving 972544 citations.
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TL;DR: The McCulloch-Pitts model of a neuron is extended to a more general model which allows the activity of a neurons to be a “fuzzy” rather than an “all-or-none” process, called a fuzzy neuron.
Abstract: In this paper, the McCulloch-Pitts model of a neuron is extended to a more general model which allows the activity of a neuron to be a “fuzzy” rather than an “all-or-none” process. The generalized model is called a fuzzy neuron. Some basic properties of fuzzy neural networks as well as their applications to the synthesis of fuzzy automata are investigated. It is shown that any n-state minimal fuzzy automatan can be realized by a network of m fuzzy neurons, where ⌈log2n⌉
214 citations
01 Feb 2003
TL;DR: A new fuzzy preference programming method, which obtains crisp priorities from inconsistent interval and fuzzy judgments is applied in the prioritization stage of the analytic network process, and enhances the potential of the ANP for dealing with imprecise and uncertain human comparison judgments.
Abstract: In this paper we propose a fuzzy extension of the analytic network process (ANP) that uses uncertain human preferences as input information in the decision-making process. Instead of the classical Eigenvector prioritization method, employed in the prioritization stage of the ANP, a new fuzzy preference programming method, which obtains crisp priorities from inconsistent interval and fuzzy judgments is applied. The resulting fuzzy ANP enhances the potential of the ANP for dealing with imprecise and uncertain human comparison judgments. It allows for multiple representations of uncertain human preferences, as crisp, interval, and fuzzy judgments and can find a solution from incomplete sets of pairwise comparisons. An important feature of the proposed method is that it measures the inconsistency of the uncertain human preferences by an appropriate consistency index. A prototype decision support system realizing the proposed method is developed, and its performance is illustrated by examples.
214 citations
TL;DR: Conditions for global exponential stability of free fuzzy systems with uncertain delays are derived and criteria for design of nonlinear fuzzy controllers to feedback control the stability of global non linear fuzzy systems are given.
Abstract: Global exponential stability of fuzzy control systems with delays is studied. These delays in the fuzzy control systems are assumed to be any uncertain bounded continuous functions. Stability of systems with uncertain delays is interesting since in practical applications it is not easy to know the delays exactly. Conditions for global exponential stability of free fuzzy systems with uncertain delays are derived. Criteria for design of nonlinear fuzzy controllers to feedback control the stability of global nonlinear fuzzy systems are given. Theorems are proved via the method of functional differential inequalities analysis.
214 citations
TL;DR: This paper proposes a new method based on Fuzzy K-Means clustering for reducing the size of the concept lattices and demonstrates the implementation of proposed method on two application areas: information retrieval and information visualization.
Abstract: During the design of concept lattices, complexity plays a major role in computing all the concepts from the huge incidence matrix. Hence for reducing the size of the lattice, methods based on matrix decompositions like SVD are available in the literature. However, SVD computation is known to have large time and memory requirements. In this paper, we propose a new method based on Fuzzy K-Means clustering for reducing the size of the concept lattices. We demonstrate the implementation of proposed method on two application areas: information retrieval and information visualization.
214 citations