基于BP神经网络的添加剂对准东煤灰熔融特性的影响研究

Study on influences of additive based on BP neural network on fusion characteristics of Zhundong coal ash

通过试验的方法,研究了不同助熔剂对准东煤灰熔融特性的影响,分析了不同比例的4种添加剂的影响效果。为了提高该试验的效率和经济性,文中引入神经网络的相关理论和方法,对该试验中的部分结果进行了预测。通过仿真与试验结果的对比显示,构建的BP神经网络具有较高的试验精度,预测误差小于±3%,可以有效提高类似试验效率和降低试验费用。

In this paper, different flux effects on Zhundong coal ash melting characteristics studied by the experimental method, analyzed the effect of different proportions of the g kinds of additives. In order to improve the efficiency and economy of the experiment, the theory and method of neural network were introduced in this paper.The comparison between the simulation and the experimental results shows that the BP neural network constructed in this paper has high test precision and the prediction error is less than 3% ,and can effectively improve the efficiency of test, reduce the cost of test.