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ASME Press Select Proceedings
International Conference on Advanced Computer Theory and Engineering (ICACTE 2009)
By
ISBN:
9780791802977
No. of Pages:
2012
Publisher:
ASME Press
Publication date:
2009
eBook Chapter
37 Forecasting for Reservoir's Water Flow Dispatching Based on RBF Neural Network Optimized by Genetic Algorithm
By
Yan-Gao Chen
,
Yan-Gao Chen
College of Water Resource and Hydropower Institute,
Sichuan University
,Chengdu 610065
, China
Sinohydro Bureau 7 CO.,LTD
, Chengdu 611730
, China
Search for other works by this author on:
Ma Guangwen
Ma Guangwen
College of Water Resource and Hydropower Institute,
Sichuan University
,Chengdu 610065
,China
Search for other works by this author on:
Page Count:
5
-
Published:2009
Citation
Chen, Y, & Guangwen, M. "Forecasting for Reservoir's Water Flow Dispatching Based on RBF Neural Network Optimized by Genetic Algorithm." International Conference on Advanced Computer Theory and Engineering (ICACTE 2009). Ed. Yi, X. ASME Press, 2009.
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Accurate forecasting of reservoir's water flow dispatching is very significant to reservoir's optimum dispatching. In order to realize accurate forecasting results of reservoir's water flow dispatching, RBF neural network optimized by genetic algorithm (GA-RBFNN) is proposed in the paper. Genetic algorithm is well suited for searching global optimal values in complex search space. Thus, genetic algorithm is used to dynamically optimize the training parameters of RBFNN. Based on the comparison with the forecast result from BP neural network, the proposed GA-RBFNN model has higher forecasting accuracy.
Abstract
Key Words
1 Introduction
2. RBF Neural Network Optimized by Genetic Algorithm
3. Experimental Analysis for Reservoir's Water Flow Dispatching Forecasting
4. Conclusion
References
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