| 1 |
Preliminary assessment of two spatio-temporal forecasting technics for hourly satellite-derived irradiance in a complex meteorological context
Andre M, Perez R, Soubdhan T, Schlemmer J, Calif R, Monjoly S
Solar Energy, 177, 703, 2019 |
| 2 |
Nonparametric Bayesian-based recognition of solar irradiance conditions: Application to the generation of high temporal resolution synthetic solar irradiance data
Frimane A, Soubdhan T, Bright JM, Aggour M
Solar Energy, 182, 462, 2019 |
| 3 |
Hourly forecasting of global solar radiation based on multiscale decomposition methods: A hybrid approach
Monjoly S, Andre M, Calif R, Soubdhan T
Energy, 119, 288, 2017 |
| 4 |
Predictive spatio-temporal model for spatially sparse global solar radiation data
Andre M, Dabo-Niang S, Soubdhan T, Ould-Baba H
Energy, 111, 599, 2016 |
| 5 |
On the use of the coefficient of variation to measure spatial and temporal correlation of global solar radiation
Calif R, Soubdhan T
Renewable Energy, 88, 192, 2016 |
| 6 |
A study on the minimum duration of training data to provide a high accuracy forecast for PV generation between two different climatic zones
Do MT, Soubdhan T, Robyns B
Renewable Energy, 85, 959, 2016 |
| 7 |
A robust forecasting framework based on the Kalman filtering approach with a twofold parameter tuning procedure: Application to solar and photovoltaic prediction
Soubdhan T, Ndong J, Ould-Baba H, Do MT
Solar Energy, 131, 246, 2016 |
| 8 |
Statistical parameters as a means to a priori assess the accuracy of solar forecasting models
Voyant C, Soubdhan T, Lauret P, David M, Muselli M
Energy, 90, 671, 2015 |
| 9 |
Spatial-temporal forecasting of solar radiation (vol 75, pg 607, 2015)
Boland J, Soubdhan T
Renewable Energy, 81, 952, 2015 |
| 10 |
A benchmarking of machine learning techniques for solar radiation forecasting in an insular context
Lauret P, Voyant C, Soubdhan T, David M, Poggi P
Solar Energy, 112, 446, 2015 |
