煤矿安全2017，Vol.48Issue(11)：21-25,5.DOI:10.13347/j.cnki.mkaq.2017.11.006
基于影响因素优选的煤层瓦斯渗透率预测模型
Prediction Model of Coalbed Gas Permeability Based on Optimization of Influencing Factors
摘要
Abstract
We acquired the correlation coefficients between coal seam gas permeability and its influential factors which are effective stress,temperature,compressive strength and gas pressure by correlation analysis.In addition,the influence factors of coal seam gas permeability have cross correlation among each other according to correlation analysis.The mean impact value (MIV) method was used for the optimization of influencing factors and achieved the three main influential factors affecting coal seam gas permeability which are effective stress,temperature and gas pressure,and choosing them as input variables of BP neural network for modeling based on experimental data.In this study,two models of coal seam gas permeability were established,one of them is called model 1 which was built without optimization of influencing factors and the other one is called model 2 which was built with optimization of influencing factors.Through the modeling computation and error analysis,we can safely conclude that the model 2 has better stability and higher accuracy in model predictive,and it can reflect the mapping relationship between coal seam gas permeability and its influencing factors perfectly.关键词
煤层瓦斯/渗透率/MIV算法/BP神经网络/影响因素Key words
coalbed gas/permeability/mean impact value (MIV) method/BP neural network/influence factor分类
矿业与冶金引用本文复制引用
王攀,杜文凤,冯飞胜..基于影响因素优选的煤层瓦斯渗透率预测模型[J].煤矿安全,2017,48(11):21-25,5.基金项目
国家重大科学仪器设备开发专项资助项目(2012YQ030126) （2012YQ030126）
国家自然科学基金煤炭联合基金资助项目(U1261203) （U1261203）
中国地质调查局资助项目(12120115102101) （12120115102101）
