Short term electric load forecasting using hybrid algorithm for smart cities-Reference-Cited by-同舟云学术

Short term electric load forecasting using hybrid algorithm for smart cities

Published:2020-06-08 Issue:10 Volume:50 Page:3379-3399
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Elattar Ehab E.^ORCID,Sabiha Nehmdoh A.,Alsharef Mohammad,Metwaly Mohamed K.,Abd-Elhady Amr M.,Taha Ibrahim B. M.

Funder

Taif University

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-020-01728-x.pdf

Reference44 articles.

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2. Ahmad A, Javaid N, Mateen A, Awais M, Khan Z (2019) Short-term load forecasting in smart grids: an intelligent modular approach. Energies 12(164):1–21

3. Elattar E, Goulermas J, Wu QH (2010) Electric load forecasting based on locally weighted support vector regression. IEEE Transactions on Systems, Man, and Cybernetics-Part C: Applications and Reviews 40(4):438–447

4. Papalekopulos AD, Hesterberg TC (1990) A regression-based approach to short-term system load forecasting. IEEE Transactions on Power Systems 5(4):1535–1547

5. Taylor JW, de Menezes LM, McSharry PE (2006) A comparison of univariate methods for forecasting electricity demand up to a day ahead. International Journal of Forecasting 22(1):1–16

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