A prediction model for endtemperature on VD furnace has been developed by neural network method.
应用神经网络方法建立了VD炉钢水温度预报模型。
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The problem of hot end length in actual use is proposed and a simple analysis is given, which shows the evident effect of length on pressure ration and hot endtemperature.
The power of electronic stove is chosen according began and endtemperature, volume of the heated object, for which the paper established the optimum control model of dynamic heating.