A novel deep learning intelligent clustered hybrid models for wind speed and power forecasting

Hamed H.H. Aly

doi:10.1016/j.energy.2020.118773

A novel deep learning intelligent clustered hybrid models for wind speed and power forecasting

Hamed H.H. Aly

Institutional Research Division

Research output: Contribution to journal › Article › peer-review

80 Citations (Scopus)

Original language	English
Article number	118773
Journal	Energy
Volume	213
DOIs	https://doi.org/10.1016/j.energy.2020.118773
Publication status	Published - Dec 15 2020

ASJC Scopus Subject Areas

Civil and Structural Engineering
Modelling and Simulation
Renewable Energy, Sustainability and the Environment
Building and Construction
Fuel Technology
Energy Engineering and Power Technology
Pollution
Mechanical Engineering
General Energy
Management, Monitoring, Policy and Law
Industrial and Manufacturing Engineering
Electrical and Electronic Engineering

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.energy.2020.118773

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author = "Aly, {Hamed H.H.}",

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A novel deep learning intelligent clustered hybrid models for wind speed and power forecasting

ASJC Scopus Subject Areas

UN SDGs

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