%0 Journal Article
%T Coal-and-Gas Outburst Forecast Using CCPSO and SVM<br>一种采用CCPSO-SVM的煤与瓦斯突出预测方法
%A 黄为勇
%A 邵晓根
%A 陈奎
%J 计算机科学
%D 2012
%I 
%X In order to forecast effectively coal-and-gas outburst in coal-mine,a new method for coal-and-gas outburst forecast based on CCPSO (complete chaotic particle swarm optimization) and SVM (support vector machine) was presented. With multi-fractal dimension spectrum of gas emission amount dynamic time series in the front of work-face in coal-mine being feature index, the forecasting model was constructed by using SVM. The parameters vector of the proposed model was selected and optimized by CCPSO and the criteria of CERM (classification error rate and TSSM (test sample set minimization). The experimental results show that the proposed method is effective and provides a new approach for forecasting coal-and-gas outburst in coal-mine.
%K Coal-and-gas outburst
%K Forecast
%K Support vector machine
%K Complete chaotic particle swarm optimization
%K Multi-fractal dimension spectrum<br>煤与瓦斯突出，预测，支持向量机，完全混沌粒子群优化，多重分维谱
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=32399EFB0552EFDD4DCCDC0A497BC0F5&yid=99E9153A83D4CB11&vid=7C3A4C1EE6A45749&iid=708DD6B15D2464E8&sid=CEC789B3C68C3BB3&eid=1D67BE204FBF4800&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=0