Abstract
Extracting useable information from large and complex data is one of the challenges that can be solved by data mining. The use of data mining to understand the state of research fields and the underlying technologies which are related in intricate ways is known as bibliometric analysis or "tech mining". Tech mining can help in summarizing the important research results that are valuable to researchers, industry, and decision-making. Furthermore, tech mining can be useful in showing the trends and relations of the analyzed topic. Hence, the purpose of this research is to investigate the status and the evolution of scientific studies in the field of renewable energy forecasting using Artificial Intelligence (AI) technologies. The study seeks to address the status of the scientific production indexed in Scopus based on scientometrics indicators. In total, over 25000 articles were extracted. The collected data were analyzed using R software packages. The findings show the exponential growth of this topic in the past 10 years. The most relevant sources, authors, affiliations, and countries were found. Moreover, the most recent trends and technologies were stated. It was also found that the interest in this research topic is prevalent in Asian countries especially China which has the highest number of publications and citations. Moreover, it was found that the most fund for research in this domain comes from Chinese institutions.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.