| 基于神经网络理论的河道水情预报模型 |
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| 引用本文： | 李荣,李义天.基于神经网络理论的河道水情预报模型[J].水科学进展,2000,11(4):427-431. |
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| 作者姓名： | 李荣 李义天 |
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| 作者单位： | 1.浦东新区环境保护及市容卫生局水务处, 上海201200; |
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| 基金项目： | 国家自然科学基金项目(59890200)。 |
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| 摘 要： | 河道水流运动过程特别是洪水演进过程是一个复杂的非线性动力学过程,鉴于神经网络具有很强的处理大规模复杂非线性动力学系统的能力,本文将神经网络理论用于河道水情预报的研究,以期识别水流运动变化过程与其影响因子之间的复杂非线性关系,为河道水情预报提供了一条新的途径。在此基础上建立了螺山站洪水预报的非线性动力学模型,通过分析研究得出近年来特别是1998年长江中游出现的小流量高水位现象与螺山汉口河段累计淤积有关并得到螺山站水位变化与河床淤积之间的定量关系。
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| 关 键 词： | 神经网络 河道淤积 小流量高水位 |
| 文章编号： | 1001-6791(2000)04-0427-05 |
| 收稿时间： | 1999-06-25 |
| 修稿时间： | 1999年6月25日 |
Application of the Neural Network Theory to the Flood Prediction |
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| LI Rong,Li Yi-tian.Application of the Neural Network Theory to the Flood Prediction[J].Advances in Water Science,2000,11(4):427-431. |
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| Authors: | LI Rong Li Yi-tian |
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| Institution: | 1.Pudong Environmental Protection and City Health Bureau, Shanghai 201200, China;2.Wuhan University, Key Lab. of the Water and Sediment Sciences of Ministry of Education, Wuhan 430072, China |
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| Abstract: | Flood evolution exhibits a complicated non-linear dynamical process. The neural network possesses the capability of dealing with complex non-linear dynamical systems, this paper demonstates how it can be used in flood prediction as a new approach considering the non-linear relationship between flood evolution and its factors such as discharge, channel deformation, and so on. Based on it, the neural network approach is applied to the flow prediction of Yangtze River at Luoshan station. The preliminary results suggest that the phenomenon of small discharge with high level in middle reaches of Yangtse River recently, especially in 1998, is related to the downstream aggregation. And the quantitative relations between the water level variation of Luoshan station and the downstream aggregation are obtained. |
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| Keywords: | Neural network Aggregation Higher water level with small discharge |
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