Prediction of River Water Quality Using Organic Gray Neural Network

被引：0
|
作者：
Zhu, Changjun [1 ]
Chen, Songjie [2 ]
机构：
[1] Hebei Univ Engn, Coll Urban Construct, Handan 056038, Hebei, Peoples R China
[2] Luohe Hydraul Engn Dept, Luohe 462300, Henan, Peoples R China
来源：
2008 CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-11 | 2008年
关键词：
prediction; gray neural network; BP neural network;
D O I：
10.1109/CCDC.2008.4597771
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
hi view of the defect that the gray method can only predict the tendency approximately and artificial neural network can not predict the future tendency really, a new organic gray neural network model was proposed by the advantages of GM(1,1),unbiased GM(1, 1) and BP neural network. The two groups data got from the gray model are used as the input of the neural network and the origin data are used as the output of neural network. The neural network was trained to get the optimal structure of neural network. According to the dynamic law of one river water quality in some region, the water quality was predicted in organic gray neural network model. The results show that the model had highly fitting and predicting precision advantages than other model had.
引用
收藏
页码：2481 / 2484
页数：4
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