The SAPHiR project has its group on Zotero: https://www.zotero.org/groups/4835689/saphir/

• 2024

  • Despotovic, M., Voyant, C., Garcia-Gutierrez, L., Almorox, J., & Notton, G. (2024). Solar irradiance time series forecasting using auto-regressive and extreme learning methods: Influence of transfer learning and clustering. Applied Energy, 365, 123215. https://doi.org/10.1016/j.apenergy.2024.123215

  • Baggio, Roberta, and Jean-François Muzy. “Improving Probabilistic Wind Speed Forecasting Using M-Rice Distribution and Spatial Data Integration.” Applied Energy, vol. 360, Apr. 2024, p. 122840, https://doi.org/10.1016/j.apenergy.2024.122840

• 2023
  • J. Fericean, N. Ottavi, C. Paoli, ML Nivet, PA Bisgambiglia, “Breaking Down Barriers to Data and Code Sharing in Machine Learning Research” - TERINT 2023 : 2ième rencontre scientifique sur les territoires intelligents Date : 6 et 7 Juillet 2023, Ajaccio, INSPE de Corse.
  • R. Baïle and J.-F. Muzy, “Leveraging data from nearby stations to improve short-term wind speed forecasts,” Energy, vol. 263, p. 125644, Jan. 2023, doi: 10.1016/j.energy.2022.125644 
• 2022

  • C. Paoli et al., “”SENSOR AUGMENTED WEATHER PREDICTION AT HIGH RESOLUTION” [ANR-21-CE04-0014-03]” PROJECT DMP.” Jul. 2022. Accessed: Oct. 28, 2022. [Online]. Available: https://hal.archives-ouvertes.fr/hal-03737267

  • C. Voyant, P. Lauret, G. Notton, J.-L. Duchaud, L. Garcia-Gutierrez, et G. A. Faggianelli, « Complex-valued time series based solar irradiance forecast », Journal of Renewable and Sustainable Energy, vol. 14, n? 6, p. 066502, nov. 2022, doi: 10.1063/5.0128131