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基于灰色关联与神经网络的瓦斯含量预测研究
引用本文:王来斌,沈金山,姚多喜,高锡擎.基于灰色关联与神经网络的瓦斯含量预测研究[J].安徽理工大学学报(自然科学版),2010,30(4).
作者姓名:王来斌  沈金山  姚多喜  高锡擎
作者单位:安徽理工大学地球与环境学院;安徽省矿山地质灾害防治重点实验室;
基金项目:安徽省教育厅自然科学基金,安徽省科技厅科技攻关计划重点资助项目
摘    要:为了解各影响因素对煤层瓦斯赋存规律的影响,准确预测煤层瓦斯含量,在分析潘一东勘探钻孔资料的基础上,基于灰色关联分析了影响13-1煤层瓦斯含量的各因素,确定了煤层埋深、顶板岩性、煤层厚度和地质构造是影响煤层瓦斯含量的主要因素;利用神经网络方法建立了煤层瓦斯含量预测模型,结合实际数据,对预测模型进行训练与检验。结果表明:预测精度较高,验证了基于灰色理论与神经网络预测模型的可靠性。

关 键 词:瓦斯含量  灰色关联度  神经网络  预测模型

Research on Prediction of Gas Content Base on Gray Corelation Analysis and Neural Network
WANG Lai-bin,SHEN Jin-shan,YAO Duo-xi,GAO Xi-qing.Research on Prediction of Gas Content Base on Gray Corelation Analysis and Neural Network[J].Journal of Anhui University of Science and Technology:Natural Science,2010,30(4).
Authors:WANG Lai-bin  SHEN Jin-shan  YAO Duo-xi  GAO Xi-qing
Institution:WANG Lai-bin1,2,SHEN Jin-shan1,YAO Duo-xi1,GAO Xi-qing1(1.School of Earth Science and Environmental Engineering,Anhui University of Science and Technology,Huainan Anhui 232001,China,2.Key Laboratory of Mine Geological Hazard Control,Anhui Province,China)
Abstract:In order to Rnow variour factors that affects gas regularity,and to predict gas content accurately,this paper analyses influence factors with grey relational grade base on the analysis on the exploration borehole iuformation of 13-1 seam in Panyi east coal mine.It is found that the main factors affecting gas content in the coal seam are depth of coal seam occurrence,roof lithology,thickness of coal seam and tectonic structure.A prediction model of gas content was established with neural network method,and t...
Keywords:gas content  gray relational grade  neural network  prediction model  
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