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A Bibliometric Analysis of the Last Ten Years of Fuzzy Min-Max Neural Networks

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Science, Engineering Management and Information Technology (SEMIT 2022)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1808))

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Abstract

Neural networks have been widely used in many application areas such as power systems, weather forecasting, face recognition, behaviour analysis, fingerprint identification, healthcare, fault detection, flood monitoring system, and surveillance system, and navigation. However, classic neural network methods are insufficient for real-life applications. To tackle with this problem, using the learning capability of neural networks and deduction capability of fuzzy systems, neural networks and fuzzy sets are incorporated called as NeuroFuzzy. The Fuzzy min-max neural network (FMNN) is a special type of NeuroFuzzy. In this paper, a bibliometric analysis is conducted on FMNN literature. We consider the studies that are published in the last decade due to there is a jump in this field in the last 10 years. Social network analysis results show that Chee Peng Lim, is the most influential researcher in the network. The Neurocomputing is found to be the most influential journal, publishing 12% of all publications in this field. In addition, the International Conference on Computing, Communication, and Networking Technologies is the most influential conference on FMNN. The findings of this paper can draw a road map for researchers in the FMNNs.

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Authors and Affiliations

  1. Department of Industrial Engineering, Hasan Kalyoncu University, Gaziantep, Turkey

    Ömer Nedim Kenger & Zülal Diri Kenger

  2. Department of Industrial Engineering, Gaziantep University, Gaziantep, Turkey

    Eren Özceylan

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  1. Ömer Nedim Kenger
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  2. Zülal Diri Kenger
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  3. Eren Özceylan
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Correspondence to Ömer Nedim Kenger .

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Editors and Affiliations

  1. Kharazmi University, Tehran, Iran

    Abolfazl Mirzazadeh

  2. Ankara Yıldırım Beyazıt University, Ankara, Türkiye

    Babek Erdebilli

  3. Istinye University, Istanbul, Türkiye

    Erfan Babaee Tirkolaee

  4. Poznań University of Technology, Poznań, Poland

    Gerhard-Wilhelm Weber

  5. Indian Institute of Technology Delhi, New Delhi, India

    Arpan Kumar Kar

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Kenger, Ö.N., Kenger, Z.D., Özceylan, E. (2023). A Bibliometric Analysis of the Last Ten Years of Fuzzy Min-Max Neural Networks. In: Mirzazadeh, A., Erdebilli, B., Babaee Tirkolaee, E., Weber, GW., Kar, A.K. (eds) Science, Engineering Management and Information Technology. SEMIT 2022. Communications in Computer and Information Science, vol 1808. Springer, Cham. https://doi.org/10.1007/978-3-031-40395-8_22

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