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计算逐日潜在腾发量的BP神经网络方法
Estimation of Daily Potential Evapotranspiration by BP Neural Network
【摘要】 根据新疆阿瓦提县气象站1992~2001年的气象资料,利用Penman-Monteith公式计算逐日和逐月潜在腾发量,分析其变化特性,并利用BP神经网络建立计算逐日潜在腾发量的经验模型,探讨各输入因子对模型的影响。计算结果表明,所建立的模型简单易行,精度较高,可以应用于生产实践中。
【Abstract】 With the meteorological data from 1999 to 2001 of Awati Meteorological Station in Xinjiang Province, daily and monthly potential evapotranspiration rates are estimated by Penman-Monteith equation, and their characteristics are analyzed. Empirical models to estimate daily potential evapotranspiration are then established by BP neural network method, and the effects of each factor are discussed. It is shown that the proposed models can estimate the potential evapotranspiration with sufficient accuracy and can be easily used in practice.
【关键词】 潜在腾发量;
Penman-Monteith;
BP神经网络;
【Key words】 potential evapotranspiration; Penman-Monteith; BP neural network;
【Key words】 potential evapotranspiration; Penman-Monteith; BP neural network;
【基金】 国家"973"重点基础项目(G199904350602)
- 【文献出处】 灌溉排水学报 ,Journal of Irrigation and Drainage , 编辑部邮箱 ,2004年04期
- 【分类号】S161.4
- 【被引频次】7
- 【下载频次】233