Can I read A forecasting and forewarning model for methane hazard in working face of coal mine based on LS-SVM on EtoBox?

A forecasting and forewarning model for methane hazard in working face of coal mine based on LS-SVM by Shu-gang CAO; Yan-bao LIU; Yan-ping WANG is a Engineering article available to read on EtoBox.

What is A forecasting and forewarning model for methane hazard in working face of coal mine based on LS-SVM about?

To improve the precision and reliability in predicting methane hazard in working face of coal mine, we have proposed a forecasting and forewarning model for methane hazard based on the least square support vector (LS-SVM) multi-classifier and regression machine. For the forecasting model, the methane concentration can be considered as a nonlinear time series and the time series analysis method is adopted to predict the change in methane concentration using LS-SVM regression. For the forewarning model, which is based on the forecasting results, by the multi-classification method of LS-SVM, the methane hazard was identified to four grades: normal, attention, warning and danger. According to the forewarning results, corresponding measures are taken. The model was used to forecast and forewarn the K9 working face. The results obtained by LS-SVM regression show that the forecasting have a high precision and forewarning results based on a LS-SVM multi-classifier are credible. Therefore, it is an effective model building method for continuous prediction of methane concentration and hazard forewarning in working face.

Who reads A forecasting and forewarning model for methane hazard in working face of coal mine based on LS-SVM?

Author

Shu-gang CAO; Yan-bao LIU; Yan-ping WANG

Publisher

Chinese Electronic Periodical Services; Elsevier ; Zhongguo Kuangye Daxue; Elsevier BV (ISSN 1006-1266)

Published

2008

Language

EN

Field

Engineering (Physical Sciences)