Artificial Neural Networks in Risk Management: A Bibliometric Study

Authors

  • Breno Gontijo Tavares INATEL, Nacional Institute of Telecommunications, Information Technology and Communications Center, Av. João de Camargo, 510, Centro, ZIP: 37540-000, Santa Rita do Sapucaí, Minas Gerais State, Brazil
  • Carlos Eduardo Sanches da Silva UNIFEI, Secretaria de Educação Superior do Ministério da Educação (SESU/MEC), Esplanada dos Ministérios, Bl “L”- 3º Andar, ZIP: 70047-900, Brasília, Distrito Federal State, Brazil
  • Adler Diniz de Souza UNIFEI, Federal University of Itajuba, Institute of Mathematics and Computing, BPS Ave., 1303, Pinheirinho, ZIP:37.500-903, Itajuba, Minas Gerais State, Brazil

DOI:

https://doi.org/10.30564/jbar.v4i1.2678

Abstract

This study presents a bibliometric analysis of Artificial Neural Networks in Risk Management. The study considered articles from the I.S.I. Web of Knowledge and Scopus databases, Identification of publishers, countries, periodicals and the keywords most frequently cited. We used the CiteSpace® software to analyze this material, which provides a set of features to support bibliometrics, including the reference maps. This study provides data collection on Artificial Neural Networks applied to risk management. The number of works identified in this study is significant, and in the last ten years, the number of citations has increased. We did not identify the increase in paper count within the same period.

Keywords:

Bibliometric study; Artificial neural networks; Risk management; I.S.I. Web of knowledge; Scopus

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Vol. 4 , Iss. 1 (January 2021)

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