Fuzzy neural networks enhanced evaluation of wetland surface water quality

Authors:
Lu Wang;Xin Li;Wei Cui
Affiliations:
Institute of Economics & Management, Yanshan University, Qinhuangdao 066004, China.;Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China.;Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
Venue:
International Journal of Computer Applications in Technology
Year:
2012

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Abstract

The quality of wetland surface water is a significant factor for the evaluation of the wetland ecological environment. It is also a vital basis for planning and developing wetland tourism. This paper has tried to use Fuzzy Neural Networks (FNN) as a water quality evaluation means, which combines fuzzy membership and neural network frame, to drive the model automatically update in training and leaning processes; thus it can be applied in the simulations of complex systems. The significant factors such as ammonia nitrogen, Dissolved Oxygen (DO), Chemical Oxygen Demand (COD), total nitrogen, total phosphorus and potassium permanganate are selected to indicate the evaluation performance. The experimental results show that the evaluation procedure is consistent with the objective law and the FNN increases the credibility in the assessment of wetland quality.