| 水文预报的神经网络模式分类预报方法 |
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| 引用本文： | 黄克明,张国忠.水文预报的神经网络模式分类预报方法[J].武汉大学学报(工学版),2003,36(1):21-23. |
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| 作者姓名： | 黄克明 张国忠 |
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| 作者单位： | 1. 武汉大学数学与统计学院,湖北武汉,430072
2. 武汉大学动力与机械学院,湖北武汉,430072 |
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| 摘 要： | 基于时间序列的相空间扩维思想,利用神经网络的感知器分类原理,提出一种水文预报方法.直接从水文单因素时间序列滑动生成多维空间的一个相型分布中寻求水文现象变化的规律.并利用湖北省宜昌市沮漳河洪水资料对该方法做了初步验证.
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| 关 键 词： | 水文预报 模式分类 神经网络 |
| 文章编号： | 1006-155X(2003)01-021-03 |
| 修稿时间： | 2001年8月29日 |
Pattern recognition by use of artificial neural network applied to hydrological forecasting |
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| HUANG Ke_ming\,ZHANG Guo_zhong\.Pattern recognition by use of artificial neural network applied to hydrological forecasting[J].Engineering Journal of Wuhan University,2003,36(1):21-23. |
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| Authors: | HUANG Ke_ming\ ZHANG Guo_zhong\ |
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| Affiliation: | HUANG Ke_ming\+1,ZHANG Guo_zhong\+2 |
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| Abstract: | The problem of mid_long term hydrological forecasting is researched. A set of multidimensional vecteres is formed from one dimension in hydrological time series in terms of the idea of extended dimension principle; and a pattern recognition method is developed to apply to hydrological forecasting. The Juzhang River historical flow data in Yichang of Hubei Province, have been selected for verifying annual flow forecasting. It shows that the proposed method yields a good hydrological forecasting. |
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| Keywords: | hydrological forecast pattern recognition artificial neural network |
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