DocumentCode :
2830043
Title :
Prediction of Reservior Runoff Using RBF Neural Network-Grey System United Model
Author :
Zhang, Juan ; Zhu, Changjun
Author_Institution :
Coll. of Urban Constr., Hebei Univ. of Eng., Handan, China
fYear :
2009
fDate :
11-12 July 2009
Firstpage :
43
Lastpage :
46
Abstract :
At present, classic methods are used to predict reservoir runoff, but the result is not ideal. Due to the shortages of neural network and grey system, in this paper, a grey neural network model is set up based on grey and neural network theory. The data got from the GM(1, 4) on the factors affecting the reservoir runoff is used as the input of the neural network and the origin data of reservoir runoff are used as the output of neural network which was trained to get the optimal structure of neural network. The results show that the model had highly fitting and predicting precision advantages than other model had. The case study shows that the model is quite accurate in prediction reservoir runoff, which has some project referential value.
Keywords :
grey systems; radial basis function networks; reservoirs; RBF neural network; grey neural network model; grey system; neural network optimal structure; project referential value; reservior runoff prediction; Artificial neural networks; Automatic control; Automation; Control system synthesis; Differential equations; Neural networks; Predictive models; Reservoirs; Resource management; Water resources; grey neural network; prediction; reservior runoff;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Automation and Systems Engineering, 2009. CASE 2009. IITA International Conference on
Conference_Location :
Zhangjiajie
Print_ISBN :
978-0-7695-3728-3
Type :
conf
DOI :
10.1109/CASE.2009.107
Filename :
5194386
Link To Document :
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