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Titlebook: Soft Computing Applications in Optimization, Control, and Recognition; Patricia Melin,Oscar Castillo Book 2013 Springer-Verlag Berlin Heid

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Brain Computer Interface Development Based on Recurrent Neural Networks and ANFIS Systems, based on the electric brain signals detected through a variety of modalities. Among these, electroencephalographic signals (EEG) have received considerable attention due to several factors arising on practical scenarios, such as noninvasiveness, portability, and relative cost, without lost on accu
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An Analysis of the Relationship between the Size of the Clusters and the Principle of Justifiable Gre clusters, each cluster represents a coarse granule, whereas each data point represents a fine granule. All clustering algorithms find these relationships by different means, yet the notion of the principle of justifiable granularity is not considered by any of them, since it is a recent idea in th
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Multi-Objective Hierarchical Genetic Algorithm for Modular Granular Neural Network Optimization that the proposed modular neural network approach offers advantages over existing neural network models. Finally the modular neural networks are joined using type-2 fuzzy integration, which allows having a system with a better behavior and results.
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An Analysis of the Relationship between the Size of the Clusters and the Principle of Justifiable Grir intrinsic implementation of the principle of justifiable granularity. An analysis is done with two datasets, simplefit and iris, and two clustering algorithms, subtractive and granular gravitational.
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High-Performance Architecture for the Modified NSGA-IIin the sorting process for the NSGA-II that improves the distribution of the solutions in the Pareto front. Results for five different test functions using distinct crossover and mutation operators to test performance are presented.
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