Computational Intelligence Approaches for Energy Load Forecasting in Smart Energy Management Grids: State of the Art, Future Challenges, and Research Directions

Journal article

Peer reviewed

Seyedeh Fallah, Ravinesh Deo, MOHAMMAD SHOJAFAR, M Conti and Shahaboddin Shamshirband

Energies (Basel), Vol.11(3), p.596

08/03/2018

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https://doi.org/10.3390/en11030596View

Published (Version of record)

Title: Computational Intelligence Approaches for Energy Load Forecasting in Smart Energy Management Grids: State of the Art, Future Challenges, and Research Directions
Creators: Seyedeh Fallah (Author)
Ravinesh Deo (Author)
MOHAMMAD SHOJAFAR (Corresponding Author)
M Conti (Author)
Shahaboddin Shamshirband (Author)
Publication Details: Energies (Basel), Vol.11(3), p.596
Publication Date: 08/03/2018
Grants: TagItSmart! - Smart Tags driven service platform for enabling ecosystems of connected objects, 688061, European Commission (Belgium, Brussels) - EC
Identifiers: 99541620402346; WOS:000428304300124
Academic Unit: School of Computer Science and Electronic Engineering
Language: English
Resource Type: Journal article