The number of hidden units in a BP neural network is significant in characterizing the performance of the network.It greatly influences generalization ability and learning speed.This paper proposes an improved method of determining the number of hidden nodes.The method,based on the linear correlation and linear independent relationship of the output of hidden layers,reduces the number of hidden units and the size of network.Taking the machining process parameters as the input of BP neural network and taking the completed part as the output,this paper applied the method to neural network model.The training results demonstrate the effectiveness of this method.
BP neural networkthe number of hidden nodeslinear correlationlinear independent
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