Titlebook: Computational Intelligence in Security for Information Systems 2010; Proceedings of the 3 Álvaro Herrero,Emilio Corchado,Ángel Alonso Confe

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书目名称Computational Intelligence in Security for Information Systems 2010影响因子(影响力)




书目名称Computational Intelligence in Security for Information Systems 2010影响因子(影响力)学科排名




书目名称Computational Intelligence in Security for Information Systems 2010网络公开度




书目名称Computational Intelligence in Security for Information Systems 2010网络公开度学科排名




书目名称Computational Intelligence in Security for Information Systems 2010被引频次




书目名称Computational Intelligence in Security for Information Systems 2010被引频次学科排名




书目名称Computational Intelligence in Security for Information Systems 2010年度引用




书目名称Computational Intelligence in Security for Information Systems 2010年度引用学科排名




书目名称Computational Intelligence in Security for Information Systems 2010读者反馈




书目名称Computational Intelligence in Security for Information Systems 2010读者反馈学科排名

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BSDT ROC and Cognitive Learning Hypothesis advance, it enables to find some brain’s internal parameters. Here a methodology for BSDT analysis of measured ROC curves has been developed and applied to the fitting of empirical data. It has been demonstrated that BSDT leads naturally to a cognitive (motivational) learning (‘learning-to-be-certa

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Evolving Fuzzy Classifier for Data Mining - an Information Retrieval Approachnetic programming to evolve a fuzzy classifier in the form of a fuzzy search expression to predict product quality. We interpret the data mining task as a fuzzy information retrieval problem and we apply successful information retrieval method for search query optimization to the fuzzy classifier ev

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Cervical-Spine

A Multi-agent Data Mining System for Defect Forecasting in a Decentralized Manufacturing Environmentecentralized character of such a plant fits perfectly with the approach of a control system by means of a multi-agent configuration. The agents devoted to rendering the superficial and internal defects maps, to developing and maintaining the learning context, to evaluating the coils entering the pic

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Lipreading Using ,–Gram Feature Vectorted parameters to be used for visual speech classification. We extract the lip contour using edge detection and connectivity analysis. The boundary is defined using six cubic curves. The visual parameters are used to build .-gram feature vectors. Two sets of classification experiments are performed

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