| 1 |
Random forest regression for improved mapping of solar irradiance at high latitudes
Babar B, Luppino LT, Bostrom T, Anfinsen SN
Solar Energy, 198, 81, 2020 |
| 2 |
Prediction of time series for several hours of surface solar irradiance using one-granule cloud property data from satellite observations
Watanabe T, Nohara D
Solar Energy, 186, 113, 2019 |
| 3 |
First assessment of surface solar irradiance derived from Himawari-8 across China
Shi HR, Li WW, Fan XH, Zhang JQ, Hu B, Husi LT, Shang HZ, Han XL, Song ZJ, Zhang YJ, Wang S, Chen HB, Xia XA
Solar Energy, 174, 164, 2018 |
| 4 |
Characterization of surface solar-irradiance variability using cloud properties based on satellite observations
Watanabe T, Oishi Y, Nakajima TY
Solar Energy, 140, 83, 2016 |
| 5 |
Determination of measuring sites for solar irradiance, based on cluster analysis of satellite-derived cloud estimations
Zagouras A, Kazantzidis A, Nikitidou E, Argiriou AA
Solar Energy, 97, 1, 2013 |
| 6 |
A physical rationale for generalized Angstrom-Prescott regression
Pelkowski J
Solar Energy, 83(7), 955, 2009 |
