合成材料老化与应用2018，Vol.47Issue(2)：24-27,4.
不同神经网络在橡胶配方性能预测中的应用研究
Experimental Study on Different Neural Networks in the Prediction of EPDM Formulation Performance
摘要
Abstract
The performance of four kinds of neural networks in predicting the performance of EPDM were com-pared. The experimental data were obtained by orthogonal experiment. The neural network was trained by 13 groups,and the other three groups were tested on the neural network to compare the mean square error,the maxi-mum error,the minimum error and the average error of the neural network prediction results. The results showed that the BP neural network was the best,and the prediction accuracy of tensile strength,elongation at break and tear strength were high,followed by ELMAN and RBF neural network,and the elongation and tear strength were high pre-diction accuracy,while the GRNN neural network was not suitable for the performance prediction of the compound.关键词
神经网络/橡胶性能/预测/应用Key words
artificial neural network/rubber performance/prediction/comparative analysis分类
化学化工引用本文复制引用
曾宪奎,黄年昌,张杰,李营如,高远昊..不同神经网络在橡胶配方性能预测中的应用研究[J].合成材料老化与应用,2018,47(2):24-27,4.基金项目
山东省自然科学基金资助项目(ZR2014EMM018) （ZR2014EMM018）
