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Predicting the reference evapotranspiration based on tensor decomposition

机译：基于张量分解的参考蒸散量预测

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Most of the available models for reference evapotranspiration (ET0) estimation are based upon only an empirical equation for ET0. Thus, one of the main issues in ET0 estimation is the appropriate integration of time information and different empirical ET0 equations to determine ET0 and boost the precision. The FAO-56 Penman-Monteith, adjusted Hargreaves, Blaney-Criddle, Priestley-Taylor, and Jensen-Haise equations were utilized in this study for estimating ET0 for two stations of Belgrade and Nis in Serbia using collected data for the period of 1980 to 2010. Three-order tensor is used to capture three-way correlations among months, years, and ET0 information. Afterward, the latent correlations among ET0 parameters were found by the multiway analysis to enhance the quality of the prediction. The suggested method is valuable as it takes into account simultaneous relations between elements, boosts the prediction precision, and determines latent associations. Models are compared with respect to coefficient of determination (R (2)), mean absolute error (MAE), and root-mean-square error (RMSE). The proposed tensor approach has a R (2) value of greater than 0.9 for all selected ET0 methods at both selected stations, which is acceptable for the ET0 prediction. RMSE is ranged between 0.247 and 0.485 mm day(-1) at Nis station and between 0.277 and 0.451 mm day(-1) at Belgrade station, while MAE is between 0.140 and 0.337 mm day(-1) at Nis and between 0.208 and 0.360 mm day(-1) at Belgrade station. The best performances are achieved by Priestley-Taylor model at Nis station (R (2) = 0.985, MAE = 0.140 mm day(-1), RMSE = 0.247 mm day(-1)) and FAO-56 Penman-Monteith model at Belgrade station (MAE = 0.208 mm day(-1), RMSE = 0.277 mm day(-1), R (2) = 0.975).
机译：用于参考蒸散量（ET0）估计的大多数可用模型仅基于ET0的经验公式。因此，ET0估计中的主要问题之一是时间信息和不同的经验ET0方程的适当集成，以确定ET0并提高精度。这项研究利用FAO-56 Penman-Monteith，调整后的Hargreaves，Blaney-Criddle，Priestley-Taylor和Jensen-Haise方程，利用1980年至2006年期间的收集数据估算了塞尔维亚贝尔格莱德和尼斯的两个站点的ET0。 2010。三阶张量用于捕获月，年和ET0信息之间的三向相关性。随后，通过多路分析发现了ET0参数之间的潜在相关性，从而提高了预测的质量。建议的方法很有价值，因为它考虑了元素之间的同时关系，提高了预测精度，并确定了潜在的关联。比较模型的确定系数（R（2）），平均绝对误差（MAE）和均方根误差（RMSE）。对于两个选定站点上的所有选定ET0方法，建议的张量方法的R（2）值均大于0.9，这对于ET0预测是可以接受的。 Nis站的RMSE介于0.247至0.485 mm天（-1），贝尔格莱德站的RMSE在0.277至0.451 mm day（-1）之间，而Nis的MAE介于0.140至0.337 mm day（-1）之间，且0.208至贝尔格莱德站0.360毫米天（-1）。 Nis站的Priestley-Taylor模型（R（2）= 0.985，MAE = 0.140 mm天（-1），RMSE = 0.247 mm天（-1））和FAO-56 Penman-Monteith模型在贝尔格莱德气象站（MAE = 0.208 mm天（-1），RMSE = 0.277 mm天（-1），R（2）= 0.975）。

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  • 来源
    《Theoretical and applied climatology》 |2017年第4期|1099-1109|共11页
  • 作者

    Misaghian Negin; Shamshirband Shahaboddin; Petkovic Dalibor; Gocic Milan; Mohammadi Kasra;

  • 作者单位

    Islamic Azad Univ, Mashhad Branch, Young Researchers & Elite Club, Mashhad, Iran;

    Univ Malaya, Fac Comp Sci & Informat Technol, Dept Comp Syst & Informat Technol, Kuala Lumpur 50603, Malaysia;

    Univ Nis, Teacher Training Fac, Partizanska 14, Vranje 17500, Serbia;

    Univ Nis, Fac Civil Engn & Architecture, Aleksandra Medvedeva 14, Nish 18000, Serbia;

    Univ Massachusetts, Dept Mech & Ind Engn, Amherst, MA 01003 USA;

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