Machine learning for energy consumption prediction and scheduling in smart buildings

@article{Bourhnane2020MachineLF,
  title={Machine learning for energy consumption prediction and scheduling in smart buildings},
  author={Safae Bourhnane and Mohamed Riduan Abid and Rachid Lghoul and Khalid Zine-dine and Najib Elkamoun and Driss Benhaddou},
  journal={SN Applied Sciences},
  year={2020},
  volume={2},
  pages={1-10}
}
Predicting energy consumption in Smart Buildings (SB), and scheduling it, is crucial for deploying Energy-efficient Management Systems. Most important, this constitutes a key aspect in the promising Smart Grids technology, whereby loads need to be predicted and scheduled in real-time to cope for the strongly coupled variance between energy demand and cost. Several approaches and models have been adopted for energy consumption prediction and scheduling. In this paper, we investigated available… 

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