An Improved ELM Algorithm Based on PCA Technique

This paper proposes a modified ELM algorithm named P-ELM subject to how to select the number of hidden nodes and how to get rid of the multicollinear problem in calculation based on PCA technique. By reducing the dimension of hidden layer output matrix(H) without loss of any information through PCA theory, the proposed P-ELM algorithm can not only ensure the full column rank of newly generated hidden layer output matrix(H′), but also reduce the number of hidden nodes resulting the improvement in training speed. In order to verify the effectiveness of P-ELM algorithm, the comparative simulations are performed. The simulation results illustrate the better generalization performance and the stability of the proposed P-ELM algorithm.

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