FANN-based surface water quality evaluation model and its application in the Shaoguan area

Abstract

A fuzzy neural network model is proposed to evaluate water quality. The model contains two parts: first, fuzzy mathematics theory is used to standardize the samples; second, the RBF neural network and the BP neural network are used to train the standardized samples. The proposed model was applied to assess the water quality of 16 sections in 9 rivers in the Shaoguan area in 2005. The evaluation result was compared with that of the RBF neural network method and the reported results in the Shaoguan area in 2005. It indicated that the performance of the proposed fuzzy neural network model is practically feasible in the application of water quality assessment and its operation is simple.