Application of Support Vector Machines in Coal and Gas Outburst Area Prediction
In predicting coal and gas outburst, because of coal and gas outburst insufficient samples, the knowledge -based method in coal and gas outburst prediction were restricted to some extent. The coal and gas outburst prediction model by support vector machines, which had a strong ability to identify the characteristics in a few sample of cases, was put forward to solve the problem in the paper. Factors affecting area of coal and gas outburst were withdrawn as characteristic vectors based on the genetic algorithm according to the natural conditions and the characteristics of the geologic structure. The forecast model of support vector machines was validated with the practical example. The comparison result from support vector machines forecasting and the traditional methods indicated that this SVM (support vector machines, brief named SVM) method could meet the requirement of coal and gas outburst area forecast. The study results proved the validity of the model, and laid foundation for the area forecast of the coal and gas outburst based on support vector machines.
Coal and gas outburst Support vector machines (SVM) Area prediction.
CHEN Zuyun ZHOU Lingjian WU Changfu YANG Shengqiang
Faculty of Environmental and Architectural Engineering, Jiangxi University of Science and Technology Faculty of Safety Science Engineering, China University of Mining and Technology, Xuzhou, 221008, Ch
国际会议
2010 International Conference on Mine Hazards Prevention and Control(第二届矿山灾害预防与控制国际学术会议 ICMHPC)
青岛
英文
205-210
2010-10-15（万方平台首次上网日期，不代表论文的发表时间）