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采用增加动量项和学习率自适应调整的BP算法建立了DP780钢拉伸变形行为的人工神经网络预测模型。预测结果表明:采用改进BP算法建立的人工神经网络模型能够较为准确的预测出DP780钢拉伸变形规律。
An artificial neural network prediction model of tensile deformation behavior of DP780 steel was established by using BP algorithm which adaptively adjusted the momentum and learning rate. The prediction results show that the artificial neural network model established by the improved BP algorithm can predict the tensile deformation of DP780 steel more accurately.