摘要
焦炭的质量对高炉冶炼的生产有着重要的影响,为了解决焦炭质量预测问题,提出了基于BP神经网络的质量预测算法,文中详细阐述了该模型的建立过程和实现方法,同时也给出了在进行模型处理的时候数据预处理的方法。利用人工神经网络对非线性问题的模拟能力,构建了焦炭质量预测模型,测试结果表明在100组不同类型的焦炭质量预测分析中,质量预测的精度达到了95%。
The quality of coke has a great effect on the blast furnace process.In order to solve the quality prediction of coke,the qualitative forecast method based on the BP Neural Network is proposed in this study.In this paper,the author gives details on the construction process and realization methods of the model,and offers the data preprocessing method during the model processing.Meanwhile,this study builds a quality prediction model for coke by using the analog capability of BP Neural Network to nonlinear problem.According to the test results,the quality prediction can achieve the degree of 95% among the coke quality prediction of 100 different types.
出处
《煤炭技术》
CAS
北大核心
2012年第4期247-249,共3页
Coal Technology
基金
2010年度广西教育厅科研资助项目(201012MS239)
关键词
BP神经网络
炼焦煤
质量预测
选煤
BP neural network
coking coal
quality prediction
coal selection
