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。
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.
出处
《环境科学学报》
CAS
CSSCI
CSCD
北大核心
1995年第2期186-191,共6页
Acta Scientiae Circumstantiae
关键词
人工神经网络
B-P算法
富营养化
水质
评价
neural netwrok
B-P algorithm
eutrophication
water quality assessment.
