Volume 6 Number 12 (Dec. 2011)
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JSW 2011 Vol.6(12): 2528-2534 ISSN: 1796-217X
doi: 10.4304/jsw.6.12.2528-2534

Surface Water Quality Evaluation Using BP and RBF Neural Network

Qinghua Luan1, Changjun Zhu2
1College of Water Conservancy and Hydropower,Hebei University of Engineering, Handan, 056038, China
2College of Urban Construction, Hebei University of Engineering, Handan, 056038, China

Abstract—It is very important to evaluate water quality in environment protection. Water environment is a complicated system, traditional methods cannot meet the demands of water environment protection. In view of the deficiency of the traditional methods, a BP neural network model and a RBF neural network model are proposed to evaluate water quality. The proposed model was applied to evaluate the water quality of 10 sections in Suzhou River. The evaluation result was compared with that of the RBF neural network method and the reported results in Suzhou river. It indicated that the performance of proposed neural network model is practically feasible in the application of water quality assessment and its operation is simple.

Index Terms—water quality;RBF neural network; BP neural network; evaluation


Cite: Qinghua Luan, Changjun Zhu, "Surface Water Quality Evaluation Using BP and RBF Neural Network," Journal of Software vol. 6, no. 12, pp. 2528-2534, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency: Monthly (2006-2019); Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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