首页 | 本学科首页   官方微博 | 高级检索  
     

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
引用本文: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[J]. 水资源与水工程学报, 2013, 24(3): 43-45,49
作者姓名:邓 丽 娟
作者单位:新疆水利水电科学研究院,新疆乌鲁木齐,830049
基金项目:水利部公益性行业科研专项经费项目
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。

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
收稿时间:2013-01-10
修稿时间:2013-01-31

Analysis of impact of meteorological factor on water evaporation based on neural network-default factor method and entropy method
DENG Lijuan. Analysis of impact of meteorological factor on water evaporation based on neural network-default factor method and entropy method[J]. Journal of water resources and water engineering, 2013, 24(3): 43-45,49
Authors:DENG Lijuan
Affiliation:DENG Lijuan(Xinjiang Research Institute of Water Resources and Hydropower,Urumqi 830049,China)
Abstract: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.
Keywords:neural network-default factor method  entropy method  water surface evaporation  Che'erchen river basin
本文献已被 CNKI 万方数据 等数据库收录!
点击此处可从《水资源与水工程学报》浏览原始摘要信息
点击此处可从《水资源与水工程学报》下载免费的PDF全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号