DocumentCode :
508189
Title :
Coal Mine Safety Investment Prediction Based on Support Vector Machine
Author :
Xiang, Chen ; Weihua, Cai ; Na, Chen
Author_Institution :
Hebei Univ. of Eng., Handan, China
Volume :
2
fYear :
2009
fDate :
14-16 Aug. 2009
Firstpage :
199
Lastpage :
202
Abstract :
Presently, coal mine safety situation in China is still severe. One of the most important reasons is safety investment insufficient. Safety investment prediction can provide decision basis for efficient controlling and guiding safety investment. The paper analyzed coal mine safety investment influence factors and established coal mine safety investment prediction model based on support vector machine. Finally, the paper adopted survey data of a mine in Huainan to exemplify and compare with traditional BP network, which proved the method feasibility and effectivity.
Keywords :
coal; investment; mining; safety; support vector machines; BP network; China; backpropagation network; coal mine safety investment influence factors; coal mine safety investment prediction model; support vector machine; Accidents; Artificial neural networks; Decision making; Domestic safety; Extrapolation; Investments; Neural networks; Predictive models; Risk management; Support vector machines; SVM; coal mine safety investment; index system; prediction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
Type :
conf
DOI :
10.1109/ICNC.2009.223
Filename :
5365908
Link To Document :
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