Chigarev, B. N. “Bibliometric Analysis of 2019-2021 Conference Proceedings on Artificial Intelligence and Energy Indexed in Scopus.” Energy Systems Research, vol. 5, no. 1, 2022, pp. 44–63. DOI.org (Crossref), https://doi.org/10.38028/esr.2022.01.0005.
Chigarev, B. N. “Bibliometric Analysis of 2019-2021 Conference Proceedings on Artificial Intelligence and Energy Indexed in Scopus.” Energy Systems Research, vol. 5, no. 1, 2022, pp. 44–63. DOI.org (Crossref), https://doi.org/10.38028/esr.2022.01.0005.
Chigarev, B. N. “Bibliometric Analysis of 2019-2021 Conference Proceedings on Artificial Intelligence and Energy Indexed in Scopus.” Energy Systems Research, vol. 5, no. 1, 2022, pp. 44–63. DOI.org (Crossref), https://doi.org/10.38028/esr.2022.01.0005.
Chigarev, B. N. “Bibliometric Analysis of 2019-2021 Conference Proceedings on Artificial Intelligence and Energy Indexed in Scopus.” Energy Systems Research, vol. 5, no. 1, 2022, pp. 44–63. DOI.org (Crossref), https://doi.org/10.38028/esr.2022.01.0005.
Abstract
The article presents a bibliometric analysis of conference proceedings 2019-2021 indexed in Scopus and related to the topic "Artificial Intelligence and Energy". The relevance of the topic is considered in the context of the energy transition and the application of artificial intelligence for the rational use of energy resources. A comparative analysis of the publication activity of researchers from Russia, China, India, the United States, and Indonesia on the topic in question is given. Methodologically, the emphasis for determining the subject is not on the co-occurrence of keywords, but on the clustering of documents based on the thesis that the titles of publications most briefly and fully reveal the content of the publication and allow the subject specialist to do a relevant selection of publications necessary for their research. Two tools were used in this work: Carrot2 and Clustering App (CSV Explorer). It is shown that Russian researches are characterized by the tendency of prevailing engineering problems and insufficient attention is paid to environmental, economic and social problems of using AI in the energy sector. Studies from China and the United States are of the greatest informative interest, both in terms of the relevance of their topics and the actuality of their content. Studies from India and Indonesia are more general in nature; of interest are the efforts of these countries to engage in global scientific activities.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
