A Prediction of Groundwater Quality Using Grey System Neural Network United Model

被引：2

作者：

Zhu, Changjun ^{[1
,2
]}

Hao, Zhen Chun ^{[2
]}

Ju, Qin ^{[2
]}

机构：

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

[2] Hohai Univ, Coll Hydrol & Water Resources, Nanjing 210098, Jiangsu, Peoples R China

来源：

CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年

基金：

中国国家自然科学基金;

关键词：

grey prediction; united grey neural network; groundwater quality; RBF neural network;

D O I：

10.1109/CCDC.2009.5191466

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

At present, classic methods are often used to predict groundwater level, but the result is not ideal. In view of the defect that the grey method can only predict the tendency approximately and artificial neural network can not predict the future tendency really, a new united grey neural network model was developed. This paper mainly analyses the groundwater quality and establishes their mathematical model based on the groundwater monitoring data of one area by united grey neural network method. It predicts various tendency of groundwater quality in this area in the future. Case study indicates that precision of the model is rather high and its popularization significance is better than the other models, and has some practical value when being used in the prediction of groundwater quality analysis..

引用

页码：3216 / +

页数：2

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