Application of Probabilistic Neural Network Model in Evaluation of Water Quality

被引：0

作者：

Zhu, Changjun ^{[1
]}

Hao, Zhenchun ^{[2
]}

机构：

[1] Hebei Univ Engn, Coll Urban Construct, Handan 056038, Peoples R China

[2] Hohai Univ, State Key Lab Hydrol Water Resources & Hydraul En, Nanjing 210098, Peoples R China

来源：

2009 INTERNATIONAL CONFERENCE ON ENVIRONMENTAL SCIENCE AND INFORMATION APPLICATION TECHNOLOGY,VOL I, PROCEEDINGS | 2009年

基金：

中国国家自然科学基金;

关键词：

water quality evaluation; probabilistic neural networks; surface water;

D O I：

10.1109/ESIAT.2009.36

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In view of the defect of traditional water quality evaluation model, a probabilistic neural network (PNN) is developed to evaluate surface water quality in Jining. Probabilistic neural network is a new type neural network consisting Radical Basis network and compete neural network, which is simple in structure, easy for training and wide used. PNN model is applied to evaluate water quality at representative sections in Jining surface area from the year 1999-2002. The results indicate that PNN model is suitable for water quality evaluation. By analysis, it is important to pay attention to bring into effective measures for pollution control.

引用

页码：244 / +

页数：2

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