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Web mining based on chaotic social evolutionary programming algorithm
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作者 Xie Bin 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2008年第6期1272-1276,共5页
With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evoluti... With an aim to the fact that the K-means clustering algorithm usually ends in local optimization and is hard to harvest global optimization, a new web clustering method is presented based on the chaotic social evolutionary programming (CSEP) algorithm. This method brings up the manner of that a cognitive agent inherits a paradigm in clustering to enable the cognitive agent to acquire a chaotic mutation operator in the betrayal. As proven in the experiment, this method can not only effectively increase web clustering efficiency, but it can also practically improve the precision of web clustering. 展开更多
关键词 web clustering chaotic social evolutionary programming K-means algorithm
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ERBF network with immune clustering
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作者 宫新保 臧小刚 周希朗 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2004年第3期315-318,共4页
Based on immune clustering and evolutionary programming(EP), a hybrid algorithm to train the RBF network is proposed. An immune fuzzy C-means clustering algorithm (IFCM) is used to adaptively specify the amount and in... Based on immune clustering and evolutionary programming(EP), a hybrid algorithm to train the RBF network is proposed. An immune fuzzy C-means clustering algorithm (IFCM) is used to adaptively specify the amount and initial positions of the RBF centers according to input data set; then the RBF network is trained with EP that tends to global optima. The application of the hybrid algorithm in multiuser detection problem demonstrates that the RBF network trained with the algorithm has simple network structure with good generalization ability. 展开更多
关键词 immune clustering algorithm evolutionary programming RBF network.
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