• 关键词：人工神经网络  B－P算法  富营养化  水质评价

• 基金项目：

• 李祚泳
• 成都气象学院,成都 610041

• 摘要：选取与TSI_c为0.50,100相应的水质营养状态作为3个建模样本,以chl-a,TP,TN和SD4个水质参数作为样本的输入特征,建立B-P网络的水质营养状态评价模型。该模型应用于全国30个湖泊水质的营养状态评价,获得了较好的检验效果。

• Abstract：Taking three trophic states of water quality corresponding to TSI_c 0, 50, 100 as three modeling samples,and the water quality parameters of chl-a, TP, TN and SD as input pa-rameters,a model of water quality assessment for trophic state based on B-P neural network was developed.Verification of trophic state assessment for water quality of 30 lakes in China was conducted as well.

• Key words：neural netwrok  B-P algorithm  eutrophication  water quality assessment

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