Coal Mine Safety Forecast Based on Least Square Support Vector Machine

被引：0
|
作者：
Zhang Shuiping [1 ]
机构：
[1] Anhui Univ Sci & Technol, Sch Econ & Management, Hefei 232001, Peoples R China
来源：
MANAGEMENT ENGINEERING AND APPLICATIONS | 2010年
关键词：
Coal mine system safety; Small sample condition; Least Square Support Vector Machine (LS-SVM); Non-linear forecast;
D O I：
暂无
中图分类号：
S2 [农业工程];
学科分类号：
0828 ;
摘要：
Based on Least Squares Support Vector Machine (LS-SVM), a non-linear model of coal mine system safety forecast is suggested in the paper, and its procedure is also presented in detail. According to structure risk minimization, the model can desirably treat the small-sample learning and efficiently solve the difficulties in forecasting coal mine system safety by previous forecasting models. Forecast simulation experiments show the model is of higher forecasting precision, higher speed, and easy realization. Therefore, accuracy and reliability of coal mine system safety forecast can be promoted effectively.
引用
收藏
页码：434 / 439
页数：6
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