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以铸钢奥氏体形成的两个关键温度为研究对象,利用BP人工神经网络成功预测了奥氏体开始转变温度、全部转变结束温度,分析了合金元素对两个温度点的影响。方法弥补了传统经验公式预测的缺陷,是一种可靠的奥氏体形成温度预测方法。
Taking the two key temperatures of austenite formation as the object of study, BP artificial neural network was used to predict the onset temperature of austenite and the temperature of all transformation ends. The effects of alloying elements on the two temperature points were analyzed. The method makes up for the shortcoming of the traditional empirical formula prediction and is a reliable prediction method of austenite formation temperature.