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- W2380780010 abstract "Based on the experimental data obtained from 71 steel plates rolled in 4200 rolling mill,this paper established a RBF neural network prediction model of influential coefficient in stressed state by Matlab neural network toolbox.By analyzing influential factors of coefficient of stressed state and taking into account the traditional mathematical model,this paper affirmed the parameters of input layer,and by selecting suitable spread in function-newrb(),this paper affirmed the best form of the network,and as a result,it improved the prediction accuracy and the adaptability of the network.The results of testing the model indicated that the model based on RBF neural network has a good generalizing capability.Compared with traditional BP network,the result indicated that RBF has better accuracy and adaptability of the network." @default.
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- W2380780010 date "2007-01-01" @default.
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- W2380780010 title "The Model of Influential Coefficient in Stressed State of Medium and Heavy Plate Rolling Mill Based on RBF Neural Network" @default.
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