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基于BP神经网络建立轧后控制冷却主要参数和目标参量之间的关系并对模型进行训练 ,实现轧后控制冷却终冷温度和冷却速度的预测。利用现场实测数据仿真表明 ,模型有效提高了预测精度。
Based on BP neural network, the relationship between the main parameters of controlled cooling after rolling and the target parameters is established and the model is trained to predict the final cooling temperature and the cooling rate after rolling. The simulation results show that the model effectively improves the prediction accuracy.