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Artificial Neural Network Modeling the Tensile Strength of Hot Strip Mill Products

机译:人工神经网络对热轧机产品的拉伸强度建模

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摘要

In this study, the effects of chemical composition and process parameters on the tensile strength of hot strip mill products were modeled by Artificial Neural Network (ANN). A good performance of network was achieved when compared with the experimental data taken from Mobarakeh Steel Company (MSC). Moreover, the relative importance of each input variable was evaluated by sensitivity analysis. The results are evaluated based on metallurgical phenomena of steels. Therefore, it is proposed that, this model can be employed as a guide to predict the final mechanical properties of commercial low carbon steel products.
机译:在这项研究中,化学成分和工艺参数对热轧厂产品抗拉强度的影响是通过人工神经网络(ANN)建模的。与从Mobarakeh钢铁公司(MSC)获得的实验数据相比,该网络具有良好的性能。此外,通过敏感性分析评估了每个输入变量的相对重要性。根据钢的冶金现象评估结果。因此,建议将该模型用作预测商品低碳钢产品最终机械性能的指南。

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