Bibliometric Mapping and Research Development Strategies on Ensemble Spatial Regression Models
Keywords:
Bibliometric Analysis, Ensemble Spatial Regression Models, VOSviewer, Research Development StrategiesAbstract
In previous research, bibliometric analysis has been widely applied to various research topics, but there has been no research specifically discussing the development of ensemble spatial regression model research. This study aims to analyze the development of research in order to formulate strategies for future research on the topic of ensemble spatial regression models. The method used is a bibliometric approach to research publications on ensemble spatial regression models. The dataset consisted of 1,311 documents retrieved from the Scopus database for the 2007–2026 period and was analyzed using a bibliometric approach through the bibliometrix package in R, while bibliometric network mapping was visualized using VOSviewer. The results of the study indicate that the number of publications has increased significantly year over year. The United States of America and China are the countries with the highest number of citations in this study. Bibliometric network mapping shows that research on ensemble spatial regression models is frequently conducted using machine learning, spatial analysis, and regression analysis approaches. Based on the research results, the topic of ensemble spatial regression models holds potential for further development, particularly in approaches that integrate spatial analysis with ensemble methods which have not yet been widely utilized within a single study. This provides insights for formulating strategies to advance future research on ensemble spatial regression models, with a focus on topics that have not yet been extensively addressed.
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