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Titlebook: MICAI 2006: Advances in Artificial Intelligence; 5th Mexican Internat Alexander Gelbukh,Carlos Alberto Reyes-Garcia Conference proceedings

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A Connectionist Fuzzy Case-Based Reasoning Modelproblem solver. Numeric predictive attributes are modeled in terms of fuzzy sets to define neurons in an associative Artificial Neural Network (ANN). After the Fuzzy-ANN is trained, its weights and the membership degrees in the training examples are used to automatically generate a local distance fu
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Applications of Gibbs Measure Theory to Loopy Belief Propagation Algorithmgraphs, where one can use higher-order potentials. Consequently, we show beliefs are just marginal probabilities for a certain Gibbs measure on a computation tree. We also give a convergence criterion using this tree. Second, to see the usefulness of this approach, we apply a well-known general cond
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Properties of Markovian Subgraphs of a Decomposable Graphllection . of its Markovian subgraphs, we show that the set . of the intersections of all the neighboring cliques of . contains .. We also show that . holds for a certain type of . which we call a maximal Markovian supergraph of .. This graph-theoretic result is instrumental for combining knowledge structures that are given in undirected graphs.
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Answer Set General Theories and Preferencesch allow us to express preferences for general theories. The formalism used to develop our work is Answer Set Programming. Two distinct semantics for preference logic programs are proposed. Finally, some properties that help us to understand these semantics are also presented.
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A Fault Detection System Design for Uncertain T-S Fuzzy Systemsints. In order to generate a residual signal, we used a left coprime factorization of the T-S fuzzy system. Using a multi-objective filter, the fault occurrence can be detected effectively. A simulation study with nuclear steam generator level control system shows that the suggested method can be applied to detect the fault in actual applications.
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https://doi.org/10.1007/11925231Algorithms; bioinformatics; classification; computer vision; evolution; evolutionary algorithm; image proc
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978-3-540-49026-5Springer-Verlag Berlin Heidelberg 2006
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MICAI 2006: Advances in Artificial Intelligence978-3-540-49058-6Series ISSN 0302-9743 Series E-ISSN 1611-3349
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