Titlebook: Simulated Evolution and Learning; 6th International Co Tzai-Der Wang,Xiaodong Li,Xin Yao Conference proceedings 2006 Springer-Verlag Berlin

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M. Middlemiss,P. A. Whighamesented has been informed and revised over 30 years of teach.This volume contains twenty-six lectures on basic anatomy and physiology for first-year university students. Topics included are standard for anatomy and physiology courses, including cells and tissues, a brief review of chemistry, thermor

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SunJun Liu,Tao Li,Kui Zhao,Jin Yang,Xun Gong,JianHua Zhangesented has been informed and revised over 30 years of teach.This volume contains twenty-six lectures on basic anatomy and physiology for first-year university students. Topics included are standard for anatomy and physiology courses, including cells and tissues, a brief review of chemistry, thermor

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Kernel Matching Pursuit Based on Immune Clonal Algorithm for Image Recognition select algorithm, which combines the global optimal searching ability and the locally quickly searching ability in search basic function data in function dictionary, this method can reduces computational complexity of basic matching pursuits algorithm. As compared with kernel matching pursuits the

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大炮

Ensemble Learning Classifier System and Compact Rulesetemble architecture of LCS (LCSE) is described in order to improve the generalization ability of the original LCS. Secondly, an algorithm is presented for compacting the final classifier population set in order to improve the readability of LCSE, which is an amendatory version of CRA brought by Wilso

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The Role of Early Stopping and Population Size in XCS for Intrusion Detectiont uses genetic algorithms and reinforcement learning techniques. In traditional machine learning (ML), early stopping has been investigated extensively to the extent that it is now a default mechanism in many systems. However, there has been a belief that EC methods are more resilient to overfitting

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Improving Radial Basis Function Networks for Human Face Recognition Using a Soft Computing Approachystem using a soft computing approach. The performance of the present method has been evaluated using the BioID Face Database and compared with traditional radial basis function neural networks. The new approach produces successful results and shows significant recognition error reduction and learni