文献类型：期刊文献

中文题名：基于BP神经网络的T91钢蠕变行为预测研究

英文题名：Creep Behavior Prediction Research on T91 Steel Based on BP Neural Network

作者：王卫锋[1];田亮[1]

机构：[1]新乡学院计算机与信息工程学院

第一机构：新乡学院计算机与信息工程学院

年份：2013

卷号：42

期号：14

起止页码：31-33

中文期刊名：热加工工艺

外文期刊名：Hot Working Technology

收录：CSTPCD;;Scopus;北大核心:【北大核心2011】；CSCD:【CSCD2013_2014】；

语种：中文

中文关键词：蠕变速率;BP神经网络;T91钢

外文关键词：creep rate; BP neural network; T91 steel

摘要：基于BP神经网络的理论,建立了多应力水平下T91钢蠕变速率预测模型。通过实验采集到了相关实验结果,利用建立的BP神经网络模型,对实验结果数据进行训练。结果表明:模拟结果与实测结果吻合良好,预测精度很高;采用BP神经网络法可为研究T91钢蠕变行为提供一条可行方法,根据该模型可改善材料的工艺。
Based on BP neural network theory, the creep rate prediction model of T91 steel was established under multiple stress levels. By obtained experimental results and using the model, the experimental results were trained. The results show that the simulation results match the measured results well with the high forecast precision. The BP neural network method can be served as a research on T91 steel creep behavior, and the material fabrication process was improved based on the prediction model.