| 基于人工神经网络的黄河下游枯季径流预测研究 |
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| 引用本文： | 赵全升,杨天行,詹志习.基于人工神经网络的黄河下游枯季径流预测研究[J].吉林大学学报(地球科学版),2001,31(3):268-272. |
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| 作者姓名： | 赵全升 杨天行 詹志习 |
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| 作者单位： | 1. 吉林大学朝阳校区应用理学院,
2. 黄河水利委员会勘测规划设计研究院, |
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| 摘 要： | 通过分析黄河下游枯季径流的影响因素 ,主要为花园口水文站径流量和下游的引黄量这两个因子 ,花园口水文站径流量和下游的引黄量可作为输入层中的影响因子 ,下游利津站的流量作为输出层。应用多层前向人工神经网络理论 ,构造四套枯季径流实时预测的BP神经网络模型 ,使用花园口—利津水文站 2 6年的完整序列测流资料训练和检验网络并用于预测
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| 关 键 词： | 黄河下游 BP神经网络 枯季径流 预测 |
| 文章编号： | 1008-0058(2001)03-0268-05 |
| 修稿时间： | 2000年12月13日 |
RESEARCH ON DRY SEASON RUN-OFF PREDICTION IN THE LOWER YELLOW RIVER BASED ON THE NEURAL NETWORK |
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| ZHAO Quan_sheng ,YANG Tian_xing ,ZHAN Zhi_xi.RESEARCH ON DRY SEASON RUN-OFF PREDICTION IN THE LOWER YELLOW RIVER BASED ON THE NEURAL NETWORK[J].Journal of Jilin Unviersity:Earth Science Edition,2001,31(3):268-272. |
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| Authors: | ZHAO Quan_sheng YANG Tian_xing ZHAN Zhi_xi |
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| Institution: | ZHAO Quan_sheng 1,YANG Tian_xing 1,ZHAN Zhi_xi 2 |
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| Abstract: | By analyzing the influence factors of dry season run-off in the lower Yellow River, it is clear that Huayuankou station runoff discharge and supporting water are influence factors. This two factors are regarded as input layer, Lijin station runoff discharge is output layer. According to the influence factors analysis and by applying the Artificial Neural Network theory, four BP models were established. The models are trained and tested by using data of 26 years of Huayuankou station and Lijin station. BP models of dry season runoff prediction in the lower Yellow River are set up to predict the dry season run-off in the lower Yellow River. |
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| Keywords: | lower Yellow River BP neural network dry season run-off prediction |
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