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This paper proposes a new robust fuzzy CMAC algorithm for function approximation. The advantages of CMAC neural network are fast learning convergence, capable of mapping nonlinear functions quickly due to its local generalization of weight updating. In this paper, in order to overcome the problems of function approximation for a nonlinear system with noise and outliers, a robust fuzzy clustering method...
AdaBoost has been the representation of ensemble learning algorithm because of its excellent performance. However, due to its longtime training, AdaBoost was complained about by people and this defect limits the practical application. Bagging is a rapid method of training and supports for parallel computing. One of important factors that can affect the performance of ensemble learning is the diversity...
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