Artificial Immune Networks Based Radial Basic Function Neural Networks Construction Algorithm and Application

@article{Zhong2007ArtificialIN,
  title={Artificial Immune Networks Based Radial Basic Function Neural Networks Construction Algorithm and Application},
  author={Jiang Zhong and Yong Feng and Chunxiao Ye and Ling Ou and Zhiguo Li},
  journal={Third International Conference on Natural Computation (ICNC 2007)},
  year={2007},
  volume={1},
  pages={104-107}
}
An RBFNN can be regarded as a feedforward artificial neural network with a single layer of hidden units, whose responses are the output of radial basis functions (RBFs). The central problem in training a radial basis function neural network is the selection of hidden layer neurons, which includes the selection of the center and width of those neurons. In this paper, we propose a method to select hidden layer neurons based on multiple granularities immune network, and then, training a cosine RBF… CONTINUE READING

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