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Titlebook: Artificial Intelligence and Soft Computing; 12th International C Leszek Rutkowski,Marcin Korytkowski,Jacek M. Zurad Conference proceedings

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Das selbstständige Beweisverfahrento each particle in population. This new multiple choice particle swarm optimization (MC-PSO) algorithm is tested on four different test functions and the promising results of this alternative strategy are compared with the classic method.
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Das selbstständige Beweisverfahrenete chaotic Lozi map is used as the chaotic pseudo random number generator to drive the mutation and crossover process in DE. The results obtained are compared with original reactor geometry and process parameters adjustment. The statistical analysis of the results given by chaos driven DE is compared with canonical DE strategy.
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Das selbstständige Beweisverfahrend for classification tasks. Various combinations of the algorithms are experimentally evaluated as data preprocessing for regression tree induction. The influence of the instance selection algorithms and their parameters on the accuracy and rules produced by regression trees is evaluated and compared to the results obtained with tree pruning.
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https://doi.org/10.1007/978-3-663-11953-1 pair of its lower and upper approximation. Notions of lower and upper bicluster approximation are derived from the Pawlak rough sets theory. Every considered discrete value in the data can be covered with more than one rough bicluster. The presented algorithm is hierarchical, so the number of biclusters can be controlled by the user.
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Die Berechnung des Gegenstandswerteson models. In contrast to the typical top-down approaches it globally searches for the best tree structure, splitting hyper-planes in internal nodes and models in the leaves. The general structure of proposed solution follows a typical framework of evolutionary algorithms with an unstructured popula
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