Title :
Prediction and research of coal and gas outburst based on radial basis function neural networks
Author :
Hong-Feng, Ma ; Jian-Wu, Dang ; Xin, Wang
Author_Institution :
Dept. of Electron. & Inf. Eng., LAN Zhou Jioatong Univ., Lan Zhou, China
Abstract :
It is of great theoretical and practical significance of the coal and gas outburst prediction. Through the study of the original samples and the example analysis of the Predictable samples, coal and gas outburst prediction based on artificial neural network model is studied. According to the characteristics of coal and gas outburst and coal and gas outburst data indicators, a coal and gas outburst prediction of the radial basis function neural network model is established. Experiments show that the use of radial basis function neural network model can overcome the shortcomings of instability and inaccurate in the coal and gas outburst prediction, so it has more extensive application value.
Keywords :
coal; natural gas technology; radial basis function networks; artificial neural network; coal outburst prediction; gas outburst prediction; outburst data indicators; predictable samples; radial basis function neural networks; Artificial neural networks; Educational institutions; Electronic mail; Information science; Local area networks; Neural networks; Predictive models; Radial basis function networks; RBF neural network; coal and gas outburst; prediction;
Conference_Titel :
Mechanic Automation and Control Engineering (MACE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-7737-1
DOI :
10.1109/MACE.2010.5535948