DocumentCode :
2440965
Title :
SVM-based Oil Security Pre-warning
Author :
Yong-bo Sun ; Hua Zhang ; Yong-heng Lu
Author_Institution :
Heilongjiang Inst. of Sci. & Technol.
fYear :
2008
fDate :
27-28 Dec. 2008
Firstpage :
55
Lastpage :
59
Abstract :
The highly efficient and accurate oil security pre-warning is of important significance for China, a big consumption nation, to establish the scientific safeguarding countermeasures. The SVM approach was employed herein to make empirical analysis on the oil security based on the optimal selection of oil security pre-warning indices. The results show that the oil security will be under the exposure of serious warning area in 2010, 2015, and 2020, which requires enhancing the security safeguarding measures. Finally the corresponding policies and suggestions were proposed based on the analysis above.
Keywords :
forecasting theory; petroleum industry; support vector machines; SVM-based oil security pre-warning; oil security pre-warning indices; optimal selection; scientific safeguarding countermeasures; support vector machines; Area measurement; Neural networks; Petroleum; Power generation economics; Rockets; Security; Statistics; Sun; Support vector machine classification; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modelling, Simulation and Optimization, 2008. WMSO '08. International Workshop on
Conference_Location :
Hong Kong
Print_ISBN :
978-0-7695-3484-8
Type :
conf
DOI :
10.1109/WMSO.2008.68
Filename :
4756956
Link To Document :
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