A Novel Deep Learning Architecture Based IoT Time-Series for Energy Consumption Forecasting in Smart Households

Author:

El Motaki Saloua,Hirchoua Badr

Publisher

Springer International Publishing

Reference34 articles.

1. Efficacité énergétique dans le bâtiment. https://www.amee.ma/fr/expertise/batiment. Accessed 2021-07-05

2. Energy consumption in households. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=Energy_consumption_in_households. Accessed 2021-07-05

3. Energy consumption of the residential sector in the United States from 1975 to 2020. https://www.statista.com/statistics/183625/us-residential-sector-energy-consumption-from-2000/. Accessed 2021-07-05

4. Shi H, Xu M, Li R (2017) Deep learning for household load forecasting a novel pooling deep RNN. IEEE Trans Smart Grid 9(5):5271–5280

5. Almalaq A, Edwards G (2017) A review of deep learning methods applied on load forecasting. In: 2017 16th IEEE international conference on machine learning and applications (ICMLA). IEEE, pp 511–516

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