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Forty Years of Computational Intelligence: A Bibliometric Retrospective.

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Title: Forty Years of Computational Intelligence: A Bibliometric Retrospective.
Authors: Saqlain, Muhammad1,2 (AUTHOR), Merigó, José M.2 (AUTHOR) jose.merigo@uts.edu.au, Kumam, Poom1 (AUTHOR) poom.kum@kmutt.ac.th, Inkpen, Diana3 (AUTHOR)
Source: Computational Intelligence. Apr2026, Vol. 42 Issue 2, p1-35. 35p.
Subjects: Computational intelligence, Bibliometrics, Machine learning, Deep learning, Cooperative research, Artificial intelligence, Big data
Abstract: In 2025, the Computational Intelligence journal celebrates the 40th anniversary. Motivated by this event, this paper conducts a bibliometric analysis of the journal between 1985 and 2024 by using the Scopus and Web of Science databases. The aim is to explore the research trends, development, topic clusters, and key contributors in Computational Intelligence. The study also employs the VOSviewer and bibliometrix software to visualize co‐citation networks, bibliographic coupling, and co‐occurrence patterns to map the intellectual structure of the journal. The analysis shows that early theories were introduced primarily by Canadian and American researchers, while more recent contributions are increasingly coming from developing countries such as China and India, reflecting the global changing research trends. The exploration reveals the evolution of topics over time, highlighting the transition from early symbolic artificial intelligence and logic‐based reasoning towards modern developments in deep learning, big data, and machine learning. The study highlights Computational Intelligence's past achievements while outlining its future direction, emphasizing collaboration, diversity, and innovation as key to sustaining its academic excellence. [ABSTRACT FROM AUTHOR]
Copyright of Computational Intelligence is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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  Data: <searchLink fieldCode="JN" term="%22Computational+Intelligence%22">Computational Intelligence</searchLink>. Apr2026, Vol. 42 Issue 2, p1-35. 35p.
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  Data: In 2025, the Computational Intelligence journal celebrates the 40th anniversary. Motivated by this event, this paper conducts a bibliometric analysis of the journal between 1985 and 2024 by using the Scopus and Web of Science databases. The aim is to explore the research trends, development, topic clusters, and key contributors in Computational Intelligence. The study also employs the VOSviewer and bibliometrix software to visualize co‐citation networks, bibliographic coupling, and co‐occurrence patterns to map the intellectual structure of the journal. The analysis shows that early theories were introduced primarily by Canadian and American researchers, while more recent contributions are increasingly coming from developing countries such as China and India, reflecting the global changing research trends. The exploration reveals the evolution of topics over time, highlighting the transition from early symbolic artificial intelligence and logic‐based reasoning towards modern developments in deep learning, big data, and machine learning. The study highlights Computational Intelligence's past achievements while outlining its future direction, emphasizing collaboration, diversity, and innovation as key to sustaining its academic excellence. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Computational Intelligence is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1111/coin.70201
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      – Code: eng
        Text: English
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        PageCount: 35
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        Type: general
      – SubjectFull: Bibliometrics
        Type: general
      – SubjectFull: Machine learning
        Type: general
      – SubjectFull: Deep learning
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      – SubjectFull: Cooperative research
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      – SubjectFull: Artificial intelligence
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      – SubjectFull: Big data
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      – TitleFull: Forty Years of Computational Intelligence: A Bibliometric Retrospective.
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              Text: Apr2026
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              Y: 2026
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