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| 基于BP神经网络的河道断面变形预测模型 | |
| 引用本文： | 张小峰,谈广鸣,许全喜,石国钰.基于BP神经网络的河道断面变形预测模型[J].水利学报,2002,33(11):0008-0013. |
| 作者姓名： | 张小峰 谈广鸣 许全喜 石国钰 |
| 作者单位： | 1. 武汉大学水利水电学院,水沙科学教育部重点实验室,湖北,武汉,430072 2. 武汉大学水利水电学院,水沙科学教育部重点实验室,湖北,武汉,430072;长江水利委员会水文局,湖北,武汉,430010 3. 长江水利委员会水文局,湖北,武汉,430010 |
| 基金项目： | 科技部“863计划”和世界银行资助ANFAS项目，教育部科技研究重点项目 (0 2 13 4)，武汉大学科技创新基金 |
| 摘 要： | 采用“试错法”，以及通过建立网络训练学习过程与网络特征参数之间的反馈机制，对BP神经网络隐含层单元数和特征参数进行优化选择。在此基础上，以河段水沙条件、水流主流位置及河道边界条件为输入向量，河道断面高程或冲淤变形为输出向量，建立了基于BP神经网络的河道断面变形预测模型。经长江中游马家咀河段实测资料验证，模型能准确模拟和预测该河段各断面的冲淤变化过程。 |
| 关 键 词： | 断面变形 BP神经网络 预测模型 |
| 文章编号： | 0559-9350(2002)11-0008-06 |
Model for predicting cross section deformation of river channel based on BP neural networks |
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| ZHANG Xiao-feng,TAN Guang-ming,XU Quan-xi,SHI Guo-yu.Model for predicting cross section deformation of river channel based on BP neural networks[J].Journal of Hydraulic Engineering,2002,33(11):0008-0013. | |
| Authors: | ZHANG Xiao-feng TAN Guang-ming XU Quan-xi SHI Guo-yu |
| Affiliation: | 1.Wuhan University;2.Bureau of Hydrology, Yangtze River Resources Commission |
| Abstract: | The hidden layers and characteristic parameters of back propagation(BP) neural networks are optimized by means of try-and-error method and the feedback mechanism between training and determination of characteristic parameters. On this basis, by using flow and sediment conditions and position of main flow and river boundary as the input vectors, using cross section elevation and variation of silting as the output vectors, the model for predicting cross section deformation of river channel is established. The validity of this model is verified by observation data. |
| Keywords: | deformation of river cross section BP neural networks model for prediction |
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