摘要
通过分析影响精炼炉冶炼过程中钢水温度变化的主要因素,利用BP人工神经网络与专家控制相结合方法,建立了精炼过程钢水温度预测模型,并利用C#语言编程实现。应用该模型对精炼炉钢水温度进行预测,对预测结果进行了统计分析。结果表明,该模型对精炼过程钢水温度的预报误差为±5℃,准确率达到85%。
This article analyzed the main factors which influence the molten steel temperature changing in refining process of the furnace,build forecasting model for molten steel temperature by the combination of BP artificial neural network and expert control and the model can be operated by use of C# language programming.The model can be used to forecast the temperature of molten steel in refining furnace and the results of statistic analysis show that the temperature deviation of molten steel in refining furnace forecasted by this model is ±5℃,the hit rate reaches 85%.
出处
《重型机械》
2010年第6期22-25,共4页
Heavy Machinery
关键词
温度预估
神经网络
专家系统
temperature forecast
neural networks
expert system
