R. Kruse

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The aim of this paper is to introduce a fuzzy control model with well{founded semantics in order to explain the concepts applied in fuzzy control. Assuming that the domains of the input{ and output variables for the process are endowed with equality relations, that reeect the indistinguishability of values lying closely together, the use of triangular and(More)
In this paper we survey the main approaches to fuzzy shell cluster analysis which is simply a generalization of fuzzy cluster analysis to shell like clusters, i.e. clusters that lie in nonlinear subspaces. Therefore we introduce the main principles of fuzzy cluster analysis rst. In the following we present some fuzzy shell clustering algorithms. In many(More)
This section investigates graphical modeling as a powerful framework for drawing inferences under imprecision and uncertainty. We survey the semantical background and relevant properties of relational, probabilistic, and possibilistic networks and consider evidence propagation in such networks as well as methods for learning them from data. Whereas the(More)
Fuzzy systems are currently being used in a wide field of industrial and scientific applications. Since the design and especially the optimization process of fuzzy systems can be very time consuming, it is convenient to have algorithms which construct and optimize them automatically. One popular approach is to combine fuzzy systems with learning techniques(More)
The author of this book is one of the best known researchers in the ®eld of interior point algorithms for linear programming and other optimisation problems. This is attested to by the long list of references in his own name included in the bibliography, the bibliography was very up to date on publications and the book bene®ts from research results(More)
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