DocumentCode
2787702
Title
Empirical analysis of the financial risk in the coal industry
Author
Shi, Jinfa ; Jiao, Hejun
Author_Institution
Zhengzhou Inst. of Aeronaut. Ind. Manage., Zhengzhou, China
fYear
2011
fDate
10-12 July 2011
Firstpage
74
Lastpage
76
Abstract
The financial pre-warning has an important bearing on the survival and development of an enterprise. Aimed at the character of the coal industry, the least squares support vector machine prediction model is given based on the principle of the statistical learning theory and structural risk minimization. The result is given that the forecasting model is effective and offers a new method to forecast the financial risk.
Keywords
financial management; learning (artificial intelligence); least squares approximations; mining industry; risk analysis; support vector machines; coal industry; empirical analysis; financial prewarning; financial risk; forecasting model; least squares support vector machine prediction model; statistical learning theory; structural risk minimization; Industries; Security; Support vector machines; coal industry; early warning analysis; least squares support vector machine;
fLanguage
English
Publisher
ieee
Conference_Titel
Service Operations, Logistics, and Informatics (SOLI), 2011 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4577-0573-1
Type
conf
DOI
10.1109/SOLI.2011.5986531
Filename
5986531
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