Prediction of gas emission quantity based on least square support vector machine

摘要：

　　Gas emission quantity has been affected by several natural factors and development of technology,which is a nonlinear and high-dimension problem.By using least square support vector machine (LSSVM),gas emission quantity in mined-out working face has been calculated,and then it has been compared and analyzed with measurement.Besides,gas emission quantity in pre-mining has been predicted.The results indicate that the higher the prediction accuracy of LSSVM is,the stronger the generalization is.

关键词： gas emission quantity least square support vector machine prediction error analysis

作者: Yuan Junwei Wang Kai Jiang Xiaogai

作者单位: China University of Mining & Technology, Beijing,10083, China;Henan Polytechnic University, Jiaozuo China University of Mining & Technology, Beijing,10083, China Henan Polytechnic University, Jiaozuo 454003,Henan,China

会议类型: 国际会议

会议名称: The First International Workshop on Hydraulic Equipment and Support Systems for Mining (第一届液压技术与矿山装备国际研讨会(IWHEM2012))

会议地点: 辽宁葫芦岛

会议语种:英文

页码: 572-576

在线出版日期: 2012-08-07（万方平台首次上网日期，不代表论文的发表时间）