Application of SVM in Analyzing the Headstream of Gushing Water in Coal Mine

作     者：YAN Zhi-gang ZHANG Hai-rong DU Pei-jun 

作者机构：School of Environment and Spatial Informatics China University of Mining ＆ Technology Xuzhou Jiangsu 221008 China 

出 版 物：《Journal of China University of Mining and Technology》 (中国矿业大学学报（英文版）)

年 卷 期：2006年第16卷第4期

页      面：433-438页

核心收录：

学科分类：0819[工学-矿业工程] 081903[工学-安全技术及工程] 08[工学] 

基　　金：Project 40401038 supported by the National Natural Science Foundation of China and 2003047 by the Top 100 Outstanding Doctoral Dissertation Foun-dation of China 

主　　题：support vector machine gushing water headstream recogmtlon H-SVMs 

摘      要：To recognize the presence of the headstream of gushing water in coal mines, the SVM (Support Vector Ma- chine) was proposed to analyze the gushing water based on hydrogeochemical methods. First, the SVM model for head- stream analysis was trained on the water sample of available headstreams, and then we used this to predict the unknown samples, which were validated in practice by comparing the predicted results with the actual results. The experimental results show that the SVM is a feasible method to differentiate between two headstreams and the H-SVMs (Hierachical SVMs) is a preferable way to deal with the problem of multi-headstreams. Compared with other methods, the SVM is based on a strict mathematical theory with a simple structure and good generalization properties. As well, the support vector W in the decision function can describe the weights of the recognition factors of water samples, which is very important for the analysis of headstreams of gushing water in coal mines.