Jianhua Dong¹, Lifeng Wu², Xiaogang Liu^{1, *}, 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 - 01 April 2020

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 (R_d). The regular meteorological data of 1966-2015 at five stations in China were taken as the input parameters (including mean average temperature (T_a), theoretical sunshine duration (N), actual sunshine duration (n), daily average air relative humidity (RH), and extra-terrestrial solar radiation (R_a)). And their estimation accuracies were subjected to… More >

Montemayor Trejo^1,* José Alfredo, Alejandro Zermeño González², Jesús Olague Ramirez¹, Rogelio Aldaco Nuncio¹, Manuel Fortis Hernández¹, Enrique Salazar Sosa^1,3, José Cruz Rodríguez Rios¹, Cirilo Vázquez-Vázquez³

Phyton-International Journal of Experimental Botany, Vol.75, pp. 47-53, 2006, DOI:10.32604/phyton.2006.75.047

Abstract The objective of this study was to analyze the effect of different population densities and corn foliage structure in the penetration of photosynthetically active radiation, and its relationship to some yield parameters. The work was developed in the spring-summer cycle 2000 at the Ranch Hill Water, located in the kilometer 154 in the highway Saltillo – Matehuala. The Prime Time maize hybrid was established in a 3x2 factorial arrengement under a completely randomized block design and three replications. Two factors were studied: as factor a, three population densities (5.5, 7.4 and 11.1 plants m^-2), and as… More >