计算机工程与应用2011，Vol.47Issue(28)：219-222,4.DOI:10.3778/j.issn.1002-8331.2011.28.061
煤与瓦斯突出的PCA-BP神经网络预测模型研究
Model for predicting coal and gas outburst based on PCA and BP neural network
摘要
Abstract
In this paper, three main factors are extracted to replace seven original factors affecting coal and gas outburst by means of principal component analysis when variance contribution is more than 85%, by which, the input parameters of BP neural network are determined.PCA-BP neural network prediction model is established, which is trained by the study samples from typical coal and gas outburst mines.In order to check feasibility and validity of the PCA-BP model,the instances of a coal mine in Yunnan province are used as predictive samples.PCA-BP model and traditional BP neural network are compared by predictive samples. Simulation results show that the PCA-BP neural network model is superior to traditional BP neural network,and meets the requirement for coal and gas outburst prediction.关键词
主成分分析/神经网络/煤与瓦斯突出/预测Key words
principal component analysis/neural network/coal and gas outburst/forecast分类
信息技术与安全科学引用本文复制引用
许新征,丁世飞,杨胜强,赵作鹏,吴祥..煤与瓦斯突出的PCA-BP神经网络预测模型研究[J].计算机工程与应用,2011,47(28):219-222,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60975039) （the National Natural Science Foundation of China under Grant No.60975039）
江苏省基础研究计划(自然科学基金)(No.BK2009093) （自然科学基金）
中国科学院智能信息处理重点实验室开放基金(No.IIP2010-1) （No.IIP2010-1）
中国矿业大学青年科研基金项目(No.2008A045). （No.2008A045）
