| 灰色动态模型群法在河流水质预测中的应用初探 |
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| 引用本文： | 李如忠,王超.灰色动态模型群法在河流水质预测中的应用初探[J].中国农村水利水电,2003(1):76-78. |
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| 作者姓名： | 李如忠 王超 |
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| 作者单位： | 1. 河海大学水文水资源及环境学院,南京市,210098;合肥工业大学资源与环境工程学院,230009
2. 河海大学水文水资源及环境学院,南京市,210098 |
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| 摘 要： | 在对原始数据序列对数变换的基础上，依据灰色系统理论，构造了由6个GM（1，1）模型组成的灰色动态模型群，并用于淮河干流枯水期氨氮浓度变化趋势预测。研究表明，灰色动态模型群法能够充分利用近期水质资料信息预测水质变化趋势；相对单个GM（1，1）模型，灰色动态模型群法能有效改善随机波动数据序列的拟合效果，提高预测精度。
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| 关 键 词： | 河流 GM（1 1）模型 灰色动态模型群 水质预测 |
| 修稿时间： | 2002年9月23日 |
Primary study on application of grey dynamic model groups for prediction of river water quality |
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| Li Ruzhong Wang Chao.Primary study on application of grey dynamic model groups for prediction of river water quality[J].China Rural Water and Hydropower,2003(1):76-78. |
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| Authors: | Li Ruzhong Wang Chao |
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| Abstract: | On the basis of logarithmic transformation of orginal data, a grey dynamic model group is established made up of six simple grey models. Then the model group is used to predict the trend of concentration of NH3 - N in Huaihe River during dry season . Study result shows that, first, the grey dynamic model group can make full use of the recent information about water quality to predict the trend of water quality state; second, on the basis of reformation of orginal sequences, this method can improve the imitation effect of random data sequences and heighten the precision of prediction result. |
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| Keywords: | grey prediction GM(1 1) model grey dynamic model group water quality prediction |
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