NDLI: ANN based on PSO for surface water quality evaluation model and its application

Content Provider	IEEE Xplore Digital Library
Author	Changjun Zhu Xiujuan Zhao Jihong Zhou
Copyright Year	2009
Description	Author affiliation: College of Urban Construction, Hebei University of Engineering, Handan, 056038, China (Changjun Zhu; Xiujuan Zhao; Jihong Zhou)
Abstract	In view of the deficiency of the traditional methods, according to the analysis of surface water in Suzhou city, a BP neural network model is proposed to evaluate water quality. Firstly The present situation and changing trends of surface water are analyzed. The structure of BP model is described and the choice of hidden layer is also optimized. Finally, the proposed model was applied to evaluate the surface water quality in Suzhou city. BP neural network is trained using PSO. The evaluation result was compared with that of the BP neural network method without training by PSO and the reported results. It indicated that the performance of proposed neural network model is practically feasible in tha application of water quality assessment and its operation is simple.
Starting Page	3264
Ending Page	3268
File Size	159358
Page Count	5
File Format	PDF
ISBN	9781424427222
DOI	10.1109/CCDC.2009.5192292
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Artificial neural networks Educational institutions Rivers PSO evaluation Hydrology BP neural network water quality Neural networks Cities and towns Water pollution Quality assessment Mathematical model
Content Type	Text
Resource Type	Article

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