Machine learning techniques for daily solar energy prediction and interpolation using numerical weather models. Martin, R., Aler, R., Valls, J. M., & Galván, I. M. Concurrency and Computation: Practice and Experience, 28(4):1261–1274, 2016.
Machine learning techniques for daily solar energy prediction and interpolation using numerical weather models [link]Paper  doi  bibtex   
@article{DBLP:journals/concurrency/MartinAVG16,
  author    = {R. Martin and
               Ricardo Aler and
               Jos{\'{e}} Mar{\'{\i}}a Valls and
               In{\'{e}}s Mar{\'{\i}}a Galv{\'{a}}n},
  title     = {Machine learning techniques for daily solar energy prediction and
               interpolation using numerical weather models},
  journal   = {Concurrency and Computation: Practice and Experience},
  volume    = {28},
  number    = {4},
  pages     = {1261--1274},
  year      = {2016},
  url       = {https://doi.org/10.1002/cpe.3631},
  doi       = {10.1002/cpe.3631},
  timestamp = {Sat, 20 May 2017 01:00:00 +0200},
  biburl    = {https://dblp.org/rec/bib/journals/concurrency/MartinAVG16},
  bibsource = {dblp computer science bibliography, https://dblp.org}
}
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