| 应用GRNN神经网络模型计算西北干旱区内陆河流域出山径流 |
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| 引用本文： | 陈仁升,康尔泗,张济世.应用GRNN神经网络模型计算西北干旱区内陆河流域出山径流[J].水科学进展,2002,13(1):87-92. |
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| 作者姓名： | 陈仁升 康尔泗 张济世 |
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| 作者单位： | 中国科学院寒区旱区环境与工程研究所, 甘肃, 兰州, 730000 |
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| 基金项目： | 中国科学院知识创新工程重大项目(KZCX1-10-03-01);国家自然科学基金重点项目(49731030) |
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| 摘 要： | 根据全球变化对2030年降水量和气温的预测结果,设置不同的气候变化情景,应用GRNN模型对黑河出山径流进行了预测。结果表明,到2030年,黑河出山径流将有小幅度的增加。随着气温的不断上升,出山年径流量最终将减少。
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| 关 键 词： | 西北 内陆河流域 出山径流 气候变化 GRNN神经网络 |
| 文章编号： | 1001-6791(2002)01-0087-06 |
| 收稿时间： | 2000-10-12 |
| 修稿时间： | 2000年10月12 |
Application of the generalized regression neural network to simulating runoff from the mountainous watersheds of inland river basins in the arid area of northwest China |
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| CHEN Ren-sheng,KANG Er-si,ZHANG Ji-shi.Application of the generalized regression neural network to simulating runoff from the mountainous watersheds of inland river basins in the arid area of northwest China[J].Advances in Water Science,2002,13(1):87-92. |
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| Authors: | CHEN Ren-sheng KANG Er-si ZHANG Ji-shi |
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| Affiliation: | Cold and Arid Regions Environment and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou 730000, China |
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| Abstract: | According to the results of globle changing in the mountainous precipitation and air temperature of Northwest China and supposing possible several conditions of the precipitation and air temperature,this paper uses the generalized regression neural network model to predict the runof of the year 2030. The predicted results show that the runoff may arise to the year 2030,but the arising degree is not large,and ultimately the runof will decrease with arising of the air temperature. |
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| Keywords: | Northwest China Inland River Basins runoff from mountainous watersheds climate change generalized regression neural network |
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