Bibliometric Analysis of Global Scientific Literature on Robust Neural Network

• Published in: 2022 IEEE International Conference on Computing, ICOCO 2022
• Main Author: Tengku T.N.A.B.; Busu M.; Kamarudin S.A.; Ahad N.A.; Mamat N.A.M.G.
• Format: Conference paper
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2022
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85148434791&doi=10.1109%2fICOCO56118.2022.10031676&partnerID=40&md5=757ffd43a4a30a60ab6f70e7f5c004f6

The study aims to present a bibliographic review of publications from the Scopus database related to the robust neural network topic. As of 13th September 2022, this study managed to gather 16 articles from 2019-2023 based on the keywords of robust neural network used for the searching process. The three tools have been used to analyze the gathered Scopus database, which are Microsoft Excel, VOSviewer software and Harzing's Publish and Perish software. This study reports the findings in terms of the current trend and the impact of publications of robust neural network studies. According to bibliometrics analysis, the number of publications has been increasing over time. This study focuses only on the Scopus database. For future research, other databases like PubMed, Lens, Dimensions, and Web of Science could be considered so the findings will be more meaningful and impactful. This study is the first article to do a bibliographic review related to the neural network. © 2022 IEEE.