Commenced in January 2007
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Edition: International
Paper Count: 1
Search results for: Xingshi He
1 Training Radial Basis Function Networks with Differential Evolution
Authors: Bing Yu , Xingshi He
Abstract:
In this paper, Differential Evolution (DE) algorithm, a new promising evolutionary algorithm, is proposed to train Radial Basis Function (RBF) network related to automatic configuration of network architecture. Classification tasks on data sets: Iris, Wine, New-thyroid, and Glass are conducted to measure the performance of neural networks. Compared with a standard RBF training algorithm in Matlab neural network toolbox, DE achieves more rational architecture for RBF networks. The resulting networks hence obtain strong generalization abilities.
Keywords: differential evolution, neural network, Rbf function
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