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FANN-Based Surface Water Quality Evaluation Model and Its Application in the Shaoguan Area
作者姓名:YANG  Meini  LI  Dingfang  YANG  Jinbo  XlONG  Wei
作者单位:School of Mathematics and Statistics Wuhan University,Luojia Hill Wuhan 430072 China
基金项目:Supported by the National Key Research Program of China (No. 2003CCA00200),the Open Research Foundation of State KeyLab of Water Resources and Hydropower Engineering Science(No.2005C012).
摘    要: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 ...

关 键 词:模糊人工神经网络  地表水  水质评价模型  韶关地区
文章编号:1009-5020(2007)04-303-08
收稿时间:2007-09-20

FANN-based surface water quality evaluation model and its application in the Shaoguan area
YANG Meini LI Dingfang YANG Jinbo XlONG Wei.FANN-Based Surface Water Quality Evaluation Model and Its Application in the Shaoguan Area[J].Geo-Spatial Information Science,2007,10(4):303-310.
Authors:Yang Meini  Li Dingfang  Yang Jinbo  Xiong Wei
Institution:School of Mathematics and Stetistics, Wuhan University, Luojia Hill, Wuhan 430072, China
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.
Keywords:fuzzy neural network  RBF neural networks  BP neural networks  water quality evaluation
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