A Novel Method to Optimize the Structure of BP Neural Networks

Changming Qiao, Shuli Sun

Abstract


It has been a long time that there is not a so good method to determine the number of neurons in hidden layer for BP neural network. For this problem, a novel algorithm based on Akaike Information Criterion (AIC) to optimize the structure of the BP neuron networks is proposed in this paper. At the same time, this paper gives the upper and lower bounds for classical AIC to overcome its shortcomings. The simulation experiment shows that this method can select a more suitable network structure, and can ensure the minimal output error with the optimal structure of the network.

 

DOI: http://dx.doi.org/10.11591/telkomnika.v11i10.3344


Keywords


BP neuron networks; AIC; network structure

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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