| Application of wavelet transform in runoff sequence analysis |
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| 引用本文： | LIU Suyi,QUAN Xianzhang,ZHANG Yongchuan. Application of wavelet transform in runoff sequence analysis[J]. 自然科学进展(英文版), 2003, 13(7): 546-549 |
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| 作者姓名： | LIU Suyi QUAN Xianzhang ZHANG Yongchuan |
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| 作者单位： | College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China,College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China,College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China |
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| 基金项目： | Supported by the National Natural Science Foundation of China (Grant No.50079006) |
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| 摘 要： | A wavelet transform is applied to runoff analysis to obtain the composition of the runoff sequence and to forecast future runoff. An observed runoff sequence is firstly decomposed and reconstructed by wavelet transform and its expanding tendency is derived. Then, the runoff sequence is forecasted by the back propagation artificial neural networks (BPANN) and by a wavelet transform combined with BPANN. The earlier researches seldom involve the problem of how to choose wavelet function, which is important and cannot be ignored when the wavelet transform is used. With application of the developed approach to the analysis of runoff sequence, several kinds of wavelet functions have been tested.
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| 关 键 词： | runoff sequence analysis wavelet transform decomposition and reconstruction back propagation arti |
Application of wavelet transform in runoff sequence analysis |
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| LIU Suyi,QUAN Xianzhang,ZHANG Yongchuan. Application of wavelet transform in runoff sequence analysis[J]. Progress in Natural Science, 2003, 13(7): 546-549 |
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| Authors: | LIU Suyi QUAN Xianzhang ZHANG Yongchuan |
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| Affiliation: | College of Hydropower and Information Engineering, Huazhong University of Science and Technology, Wuhan 430074, China |
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| Abstract: | A wavelet transform is applied to runoff analysis to obtain the composition of the runoff sequence and to forecast future runoff. An observed runoff sequence is firstly decomposed and reconstructed by wavelet transform and its expanding tendency is derived. Then, the runoff sequence is forecasted by the back propagation artificial neural networks (BPANN) and by a wavelet transform combined with BPANN. The earlier researches seldom involve the problem of how to choose wavelet function, which is important and cannot be ignored when the wavelet transform is used. With application of the developed approach to the analysis of runoff sequence, several kinds of wavelet functions have been tested. |
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| Keywords: | runoff sequence analysis wavelet transform decomposition and reconstruction back propagation arti |
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