摘要
为了准确可靠预测工作面的瓦斯涌出量,本文以卡尔曼滤波为基础,结合人工神经网络,设计虚拟中间状态变量并得出对应预测模型。其间通过Matlab使预测模型实现目的,并用此方法对某矿采煤工作面瓦斯涌出量进行预测。结果表明,建立的预测方法具有较好的预测性能,其平均误差为3.35%,结果正确可靠。
In order to accurately and reliably predict the amount of gas emission from the working face, this paper used the Kalman filter as the basis and combined the artificial neural network to design the virtual intermediate state variables and obtain the corresponding prediction model. In the meantime, the prediction model was achieved by Matlab,and the gas emission from a coal mining face was predicted by this method. The results show that the established prediction method has better prediction performance, and the average error is 3.35%, the result is correct and reliable.
作者
唐一举
TANG Yiju(Henan College of Industry&Information Technology,Jiaozuo Henan 454000)
出处
《河南科技》
2019年第29期96-98,共3页
Henan Science and Technology
关键词
卡尔曼滤波法
径向基神经网络
瓦斯涌出量
Calman filtering method
radial basis function neural network
gas emission
