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Artificial Neural Network Applied to Austenite Formation Temperature Prediction
Author(s): 
Pages: 43-47
Year: Issue:  10
Journal: HEAT TREATMENT OF METALS

Keyword:  奥氏体形成温度人工神经网络预测性能合金元素定量影响;
Abstract: 根据所收集的试验数据,建立了预测钢的奥氏体形成温度Ac3和Ac1点的反向传播人工神经网络模型.用散点图和均方误差、相对均方误差和拟合分值3种统计学指标评价模型的预测性能.人工神经网络预测Ac3和Ac1的3种统计学指标分别为23.8℃,14.6℃;2.89%,2.06%和1.8921,1.7011.散点图和统计学指标均表明人工神经网络的预测性能优于Andrews公式.此外,用人工神经网络分析了C和Mn的含量对Ac3和Ac1温度的定量影响,计算结果表明,C和Mn含量与Ac3和Ac1点间存在非线性关系.
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