文章摘要
邓 丽 娟.利用神经网络-缺省因子法及熵权法分析气象因素对水面蒸发的影响Journal of Water Resources and Water Engineering[J].,2013,24(3):43-45,49
利用神经网络-缺省因子法及熵权法分析气象因素对水面蒸发的影响
Analysis of impact of meteorological factor on water evaporation based on neural network-default factor method and entropy method
Received:January 10, 2013  Revised:January 31, 2013
DOI:
中文关键词: 神经网络-缺省因子法  熵权法  水面蒸发  车尔臣河流域
英文关键词: neural network-default factor method  entropy method  water surface evaporation  Che''erchen river basin
基金项目:水利部公益性行业科研专项经费项目(201201037)
Author NameAffiliation
DENG Lijuan Xinjiang Research Institute of Water Resources and Hydropower, Urumqi 830049, China [KH*3D] 
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中文摘要:
      根据新疆车尔臣流域且末县气象站2007年非结冰期(4-9月)日水面蒸发量及相关常规气象观测资料,利用神经网络-缺省因子法及熵权法分析了各气象要素对水面蒸发的影响程度。结果表明:水面蒸发对温度与风速最为敏感。希望从气象因素角度出发,为区域水资源优化调度提供参考。
英文摘要:
      according to daily evaporation and meteorological data during non-glacial period of 2007from Qiemo meteorological station in Che''erchen River basin of Xinjiang (April to September), the paper used neural network- the default factor method and entropy method to analyze the influence of meteorological factors on water evaporation. Results show that temperature and wind speed is the most sensitive factors on the influence of water surface evaporation. Hope from meteorological factors point of view, to provide reference for regional water resources optimal allocation.
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