Jianhua Dong1, Lifeng Wu2, Xiaogang Liu1, *, Cheng Fan1, Menghui Leng3, Qiliang Yang1
CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.1, pp. 49-73, 2020, DOI: 10.32604/cmes.2020.09014
Abstract Solar radiation is an important parameter in the fields of computer modeling,
engineering technology and energy development. This paper evaluated the ability of three
machine learning models, i.e., Extreme Gradient Boosting (XGBoost), Support Vector
Machine (SVM) and Multivariate Adaptive Regression Splines (MARS), to estimate the
daily diffuse solar radiation (Rd). The regular meteorological data of 1966-2015 at five
stations in China were taken as the input parameters (including mean average temperature
(Ta), theoretical sunshine duration (N), actual sunshine duration (n), daily average air
relative humidity (RH), and extra-terrestrial solar radiation (Ra)). And their estimation
accuracies were subjected to comparative analysis.… More >
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