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《Journal of Beijing Institute of Technology》 1998-04
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The Most Suitable Architecture of Hidden - Layer in BP Neural Networks for Function Approximation

Liao Ningfang; Gao Zhiyun (Department of Optical Engineering,Beijing Institute of Technology,Beijing 100081)  
Aim To determine the most suitable architecture of hidden-layer in an er- ror-back -propagation neural netwok for function approximation. Methods To train the typical multi-layer BP neural netwoks with different hidden layers and neurons to approximate a typical function, and analyze the results. Results The most suitable number of hidden layers in a BP neural network is 4,and the most suitable number of neurons in each hidden layer is between 10 to 20,and a BP neural network with a single hidden layer has the worst results.Conclusion For function approximation,the most suitable number of hidden layers in a BP neural network should be about 4, and there should be suitable number of neurons in each hidden layer.
【Fund】: 云南省自然科学基金
【CateGory Index】: TP18
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