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Author:

Pang, Zihan (Pang, Zihan.) | Jia, Kebin (Jia, Kebin.) (Scholars:贾克斌) | Feng, Jinchao (Feng, Jinchao.) (Scholars:冯金超)

Indexed by:

CPCI-S EI Scopus

Abstract:

The rational allocation of water resources has become an important prerequisite for the protection of national economic and social sustainable development as the China economic develops rapidly, therefore establishing water security environment monitoring and evaluation mechanisms is a good way for providing services and solutions for regional environmental management and accident pollution. Considering features of super-large water transmission engineering, water environmental safety level assessment strategy based on intelligent video surveillance is designed. According to features of main water surface and that of moving target, and by using SVM the corresponding water environment security level classification model is designed. The application of sample offline learning methods guaranteed efficiency and accuracy of water quality assessment, and the results of several kernels are also analyzed and verified via tests. This algorithm has been successfully used in the central line project of south-to-north water diversion, and the test result shows that this algorithm is of high robustness and accuracy.

Keyword:

water security environment evaluation model SVM

Author Community:

  • [ 1 ] [Pang, Zihan]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 2 ] [Jia, Kebin]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing, Peoples R China
  • [ 3 ] [Feng, Jinchao]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing, Peoples R China

Reprint Author's Address:

  • [Pang, Zihan]Beijing Univ Technol, Sch Elect Informat & Control Engn, Beijing, Peoples R China

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Source :

2014 TENTH INTERNATIONAL CONFERENCE ON INTELLIGENT INFORMATION HIDING AND MULTIMEDIA SIGNAL PROCESSING (IIH-MSP 2014)

Year: 2014

Page: 191-194

Language: English

Cited Count:

WoS CC Cited Count: 3

SCOPUS Cited Count: 6

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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