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• [P326] A Hybrid MGA-BP Algorithm for RBFNs self-generate
  Author(s): Shiwei Yu
  
  

  Abstract
  This paper proposes a novel hybrid algorithm to determine the parameters (number of neurons, centers, widths and weights) of radial basis function neural networks automatically. In this work, a hybrid algorithm combines the multi-encoding genetic algorithm (MGA) and the back propagation (BP) algorithm to form a hybrid learning algorithm (MGA-BP) for training Radial Basis Function Networks (RBFNs), which adapts to the network structure and updates its weights by choosing a special fitness function. The proposed method is used to deal with non-linear identification problems, and the results obtained are compared with existent bibliography, showing an improvement over the published methods.

  
   

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