| 基于最小二乘支持向量机的参考作物潜在蒸散量估计 |
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| 引用本文： | 陈大春,曹伟,雷晓云.基于最小二乘支持向量机的参考作物潜在蒸散量估计[J].新疆农业大学学报,2011(5):431-436. |
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| 作者姓名： | 陈大春 曹伟 雷晓云 |
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| 作者单位： | 新疆农业大学水利与土木工程学院; |
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| 基金项目： | 国家科技支撑计划项目(2007BAD38B05-03) |
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| 摘 要： | 建立了以气象因子为输入变量,以Penman-Monteith公式计算所得的参考作物潜在蒸散量（ET0）为输出变量的最小二乘支持向量机（LSSVM）ET0预报模型。与以同样资料为基础的人工神经网络模型（ANN）进行对比研究表明,LSSVM模型比ANN模型精度高,且效率高、泛化能力强,是ET0预报方法的有益补充。
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| 关 键 词： | 参考作物潜在蒸散量 LSSVM ANN |
Estimation on Daily Reference Evapotranspiration Based on Least Squares Support Vector Machines |
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| CHEN Da-chun,CAO Wei,LEI Xiao-yun.Estimation on Daily Reference Evapotranspiration Based on Least Squares Support Vector Machines[J].Journal of Xinjiang Agricultural University,2011(5):431-436. |
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| Authors: | CHEN Da-chun CAO Wei LEI Xiao-yun |
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| Institution: | CHEN Da-chun,CAO Wei,LEI Xiao-yun(College of Water Conservancy and Civil Engineering,Xinjiang Agricultural University,Urumqi 830052,China) |
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| Abstract: | The present study was designed to establish Daily reference evapotranspiration(ET0) prediction model,by which the meteorological factor was used as an input variable,the ET0 obtained with Penman-Monteith formula as Least Squares Support Vector Machine(LSSVM) of an output variable,which was compared with the Artificial Newral Network(ANN) model based on the same data.The result showed that the accuracy of LSSVM model was higher than that of ANN model,the former had high efficiency and strong generalization p... |
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| Keywords: | Daily reference evapotranspiration LSSVM ANN |
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