Support Vector Machine Regression Model of CBM Content and Appliration

摘要：

In order to quantitatively predictive the content of the coalbed methane (CBM), we make use of the known parameters of the core tests data to establish the support vector machine regression model between the core data and coal-bed methane content The model is based on the small sample size theory. Using the model, we can predict the volume of gas content We choose the coal seam thickness, coal vitrinite reflectance value and coal ash 3 parameters as input feature vectors, and coal-bed methane content as the output vector of support vector machine regression prediction model.Application of the proposed model in Binchang mining shows that the prediction error between the measured results and prediction are small and meet the accuracy requirements.

关键词： Core tests Coalbed methane content support vector machine regression

作者: TANG Hong-wei CHENG Jian-yuan WANG Shi-dong

作者单位: CCRI,Xian Branch,Shaanxi province Xian city,710054

会议类型: 国际会议

会议名称: 2009 IEEE International Conference on Intelligent Computing and Intelligent Systems(2009 IEEE 智能计算与智能系统国际会议)

会议地点: 上海

会议语种:英文

页码: 99-102

在线出版日期: 2009-11-20（万方平台首次上网日期，不代表论文的发表时间）