Akademik Veri Yönetim Sistemi
8 th HAGIA SOPHIA INTERNATIONAL CONFERENCE ON MULTIDISCIPLINARY SCIENTIFIC STUDIES, İstanbul, Türkiye, 11 - 12 Eylül 2024, ss.288-294
In this paper, publications in the literature are systematically analysed to evaluate the contributions of multi-objective optimisation to dispersion parameter estimation. The bibliometric analysis aims to identify research gaps in the literature and provide directional information for future studies. The dataset used in the study was obtained from scientific studies published on 21.08.2024 in the Web of Science (WoS) database on parameter estimation of distributions with multi-objective optimisation. In the bibliometric analysis, R Studio-Biblioshiny and Vosviewer 1.6.20 programs was used to examine countries, authors, keywords, journals and citation trends. In the study, articles, early access articles and review articles were included and a bibliometric analysis was performed on 141 scientific studies from the first study published on the subject published in 2005 to 2024. From 2005 to the present, the number of publications tends to increase according to the years and the highest number of publications was realised in 2022. It has been determined that multi-objective optimisation stands out as an important tool in parameter estimation of distributions and research in this field is increasing. Although China is the country with the highest number of publications in this field, the USA has been the country with the highest number of citations. The most commonly used keywords were ‘optimisation’ and ‘algorithm’. When joint studies between countries are analysed, the most cooperation is between China-UK and China-US.