Artificial Neural Network and its Applications in the Energy Sector An Overview

Damilola Elizabeth Babatunde, Ambrose Anozie and James Omoleye
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Damilola Elizabeth Babatunde: Department of Chemical Engineering, Covenant University, Otta, Ogun State, Nigeria.
Ambrose Anozie: Department of Chemical Engineering, Covenant University, Otta, Ogun State, Nigeria.
James Omoleye: Department of Chemical Engineering, Covenant University, Otta, Ogun State, Nigeria.

International Journal of Energy Economics and Policy, 2020, vol. 10, issue 2, 250-264

Abstract: In order to realize the goal of optimal use of energy sources and cleaner environment at a minimal cost, researchers; field professionals; and industrialists have identified the expediency of harnessing the computational benefits provided by artificial intelligence techniques. This article provides an overview of artificial intelligence (AI), chronological blueprints of the emergence of artificial neural networks (ANNs) and some of its applications in the energy sector. This short survey reveals that despite the initial hiccups at the developmental stages of artificial neural networks, ANN has tremendously evolved, is still evolving and have been found to be effective in handling highly complex problems even in the areas of modeling, control, and optimization, to mention a few.

Keywords: artificial neural networks; energy sector; optimization (search for similar items in EconPapers)
JEL-codes: P28 Q4 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eco:journ2:2020-02-31

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