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

Authors:
Changjun Zhu;Xiujuan Zhao;Jihong Zhou
Affiliations:
College of Urban Construction, Hebei University of Engineering, Handan, China;College of Urban Construction, Hebei University of Engineering, Handan, China;College of Urban Construction, Hebei University of Engineering, Handan, China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Neural network design

Neural network design
Approximation capability to functions of several variables, nonlinear functionals, and operators by radial basis function neural networks

IEEE Transactions on Neural Networks

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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 the application of water quality assessment and its operation is simple.