Application of Machine Learning in Renewable Energy: A Bibliometric Analysis of a Decade
Yükleniyor...
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/embargoedAccess
Özet
Machine learning studies in the field of renewable
energy are analysed here (REML). So, from 2012 to 2021, we
looked at the publication tendencies (PT) and bibliometric
analysis (BA) of REML research that was indexed by Elsevier
Scopus. Key insights into the research landscape, scientific
discoveries, and technological advancement were revealed by
BA, while PT highlighted REML's important players, top cited
papers, and financing organisations. In total, the PT discovered
1,218 works, 397 of which were conference papers and 106
were reviews. Because it spans the disciplines of science,
technology, engineering, and mathematics, REML research is
exhaustive, varied, and consequential. The most productive
researchers, countries, and sponsors include Ravinesh C. Deo,
the United States' National Renewable Energy Laboratory,
and China's National Natural Science Foundation. Journal
prestige and open access are valued by contributors, as seen by
the success of Applied Energy and Energies. Productivity
among REML's key stakeholders is boosted by collaborations
and research funding. Keyword co-occurrence analysis was
used to categorise REML research into four broad topic areas:
systems, technologies, tools/technologies, and socio-technical
dynamics. According to the results, ML plays a crucial role in
the prediction, operation, and optimisation of RET as well as
the design and development of RE-related materials.
Açıklama
Anahtar Kelimeler
Renewable energy, Machine learning application, Bibliometric analysis, Publication trends, technologies
Kaynak
2023 IEEE International Conference on Automatic Control and Intelligent Systems, I2CACIS 2023 - Proceedings
WoS Q DeÄŸeri
Scopus Q DeÄŸeri
N/A
