HOME JOURNALS CONTACT

Journal of Applied Sciences

Year: 2013 | Volume: 13 | Issue: 10 | Page No.: 1847-1850
DOI: 10.3923/jas.2013.1847.1850
Research on Recognition Method of Algae Blooms Based on Complex Network
Shao Fei, Wang Xiaoyi, Shi Yan, Xu Jiping, Sheng Lu, Wang Li and Tang Lina

Abstract: Based on the deep analysis of the formation process of algal blooms for the urban lakes and rivers, some key factors affecting the formation of algal blooms have been extracted. Furthermore, a recognition model of algae outbreak has been established based on the complex network to calculate the related parameters of the characters towards the complex network which is the way to achieve the recognition of the phenomenon mentioned above. By means of the experiment on the water quality in the urban lakes of Beijing, this method has been proved to be correct and efficient which provides the reference for the deeper research of the formation mechanism of algal blooms.

Fulltext PDF

How to cite this article
Shao Fei, Wang Xiaoyi, Shi Yan, Xu Jiping, Sheng Lu, Wang Li and Tang Lina, 2013. Research on Recognition Method of Algae Blooms Based on Complex Network. Journal of Applied Sciences, 13: 1847-1850.

Keywords: Complex network, algal blooms and blooms recognition

REFERENCES

  • Chau, K.W., 2005. Algal bloom prediction with particle swarm optimization algorithm. Proceedings of the International Conference on Computational Intelligence and Security, Volume 3801, December 15-19, 2005, Xi'an, China, pp: 645-650.


  • Cui, G.B., L. Li and Q. Yao, 2009. Eutrophication Control Mechanism Research in Taihu Lake. China Water Power Press, Beijing


  • Dong, S.Q. P. Liu and Y. Wang, 2012. Multi-agent modeling of algal bloom formation mechanism in lake reservoirs. Complex Syst. Complexity Sci., 01: 59-63.


  • Jia, H.F., Y.S. Zhang and M. He, 2009. Multi-species algae ecodynaic model for the beijing water system. J. Tsinghua Univ. (Natl. Sci. Edn.), 49: 1992-1996.


  • Lee, J.H.W., Y. Huang, M. Dickman and A.W. Jayawardena, 2003. Neural network modeling of coastal algal blooms. Ecol. Model, 159: 179-201.
    CrossRef    


  • Lin, S., 1965. Computer solutions of the traveling salesman problem. Bell Syst. Tech. J., 44: 2245-2269.
    Direct Link    


  • Pettersson, L.H., D. Durand, O.M. Johannessen, E. Svendsen and T. Noji et al., 2001. Monitoring and model predictions of harmful algae blooms in Norwegian waters. Proceedings of the IEEE 2001 International Geoscience and Remote Sensing Symposium, Volume 3, July 09-13, 2001, Sydney, NSW, pp: 1146-1148.


  • Tsai, C.F., C.W. Tsai and C.C. Tseng, 2004. A new hybrid heuristic approach for solving large traveling salesman problem. Inform. Sci., 166: 67-81.
    CrossRef    


  • Wang, Y., X.P. Zhao, P. Liu, J.P. Xu and S.Q. Dong, 2012. Comprehensive mechanism modeling on city lake cyanobacteria bloom formation. J. Environ. Sci., 32: 1677-1683.
    Direct Link    


  • Zaiwen, L., W. Qiaomei, W. Xiaoyi, L. Cui and X. Lian, 2008. Algal growth model based on optimized theories and its application in water bloom prediction. J. Chem. Ind. Eng., 59: 1869-1873.

  • © Science Alert. All Rights Reserved