World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
8267
World Ranking
5767
National Ranking
8

Overview

János Abonyi is affiliated with the University of Pannonia in Hungary and has contributed extensively to the fields of engineering and computer science. Their research primarily spans industrial and manufacturing engineering, with significant work also in control and systems engineering, artificial intelligence, information systems, and statistical and nonlinear physics.

Their main topics of investigation include digital transformation in industry, flexible and reconfigurable manufacturing systems, manufacturing process and optimization, fault detection and control systems, complex network analysis techniques, multi-criteria decision making, and human-automation interaction and safety.

Abonyi's recent published papers cover a range of topics connected to manufacturing systems, sustainability, and digital technologies. Notable papers include:

  • "Focal points for sustainable development strategies-Text mining-based comparative analysis of voluntary national reviews" (2020, Journal of Environmental Management)
  • "Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools" (2020, Computers in Industry)
  • "Current development on the Operator 4.0 and transition towards the Operator 5.0: A systematic literature review in light of Industry 5.0" (2023, Journal of Manufacturing Systems)
  • "Modelling for Digital Twins-Potential Role of Surrogate Models" (2021, Processes)
  • "Real-Time Locating System in Production Management" (2020, Sensors)

Their frequent coauthors include:

  • Tamás Ruppert
  • Tímea Czvetkó
  • Viktor Sebestyén
  • László Nagy
  • Alex Kummer

Abonyi's work is often published in several academic venues, including:

  • IEEE Access
  • Sensors
  • Complexity
  • Heliyon
  • PLoS ONE

They have authored books published by Springer International Publishing and Springer Nature, with titles such as Are Regions Prepared for Industry 4.0? (2020) and Ontology-Based Development of Industry 4.0 and 5.0 Solutions for Smart Manufacturing and Production (2024), as well as Network-Based Analysis of Dynamical Systems (2020).

Best Publications

  • Cluster Analysis for Data Mining and System Identification

    Janos Abonyi;Balazs Feil

  • Modified Gath-Geva fuzzy clustering for identification of Takagi-Sugeno fuzzy models

    J. Abonyi;R. Babuska;F. Szeifert

  • Supervised fuzzy clustering for the identification of fuzzy classifiers

    Janos Abonyi;Ferenc Szeifert

  • Learning fuzzy classification rules from labeled data

    Johannes A. Roubos;Magne Setnes;Janos Abonyi

  • Fuzzy Model Identification

    János Abonyi

  • Enabling Technologies for Operator 4.0: A Survey

    Tamás Ruppert;Szilárd Jaskó;Tibor Holczinger;János Abonyi

  • Fuzzy Model Identification for Control

    Janos Abonyi

  • Genetic programming for the identification of nonlinear input-output models

    János Madár;János Abonyi;Ferenc Szeifert

  • Data-driven generation of compact, accurate, and linguistically sound fuzzy classifiers based on a decision-tree initialization

    Janos Abonyi;Johannes A. Roubos;Ferenc Szeifert

  • Modified Gath--Geva clustering for fuzzy segmentation of multivariate time-series

    Janos Abonyi;Balazs Feil;Sandor Nemeth;Peter Arva

  • Effective optimization for fuzzy model predictive control

    S. Mollov;R. Babuska;J. Abonyi;H.B. Verbruggen

  • Development of manufacturing execution systems in accordance with Industry 4.0 requirements: A review of standard- and ontology-based methodologies and tools

    Szilárd Jaskó;Adrienn Skrop;Tibor Holczinger;Tibor Chován

  • Correlation based dynamic time warping of multivariate time series

    ZoltáN Bankó;JáNos Abonyi

  • Modelling for Digital Twins—Potential Role of Surrogate Models

    Ágnes Bárkányi;Tibor Chován;Sándor Németh;János Abonyi

  • Identification and Control of Nonlinear Systems Using Fuzzy Hammerstein Models

    J. Abonyi;R. Babuška;M. Ayala Botto;F. Szeifert

  • Learning Fuzzy Classification Rules from Data

    Hans Roubos;Magne Setnes;Janos Abonyi

  • Model Order Selection of Nonlinear Input-Output Models - A Clustering Based Approach

    Balazs Feil;Janos Abonyi;Ferenc Szeifert

  • Computational Intelligence in Data Mining

    Janos Abonyi;Balazs Feil;Ajith Abraham

  • Fuzzy modeling with multivariate membership functions: gray-box identification and control design

    J. Abonyi;R. Babuska;F. Szeifert

  • Real-Time Locating System in Production Management.

    András Rácz-Szabó;Tamás Ruppert;László Bántay;Andreas Löcklin

  • Inverse fuzzy-process-model based direct adaptive control

    János Abonyi;Hans Andersen;Lajos Nagy;Ferenc Szeifert

  • Local and global identification and interpretation of parameters in Takagi-Sugeno fuzzy models

    J. Abonyi;R. Babuska

  • Optimization of Multiple Traveling Salesmen Problem by a Novel Representation Based Genetic Algorithm

    András Király;János Abonyi

Frequent Co-Authors

Robert Babuska
Robert Babuska Delft University of Technology
Ahmet Palazoglu
Ahmet Palazoglu University of California, Davis
Ajith Abraham
Ajith Abraham Sai University
András Guttman
András Guttman University of Debrecen
Francisca Puertas
Francisca Puertas Spanish National Research Council
Sigurd Skogestad
Sigurd Skogestad Norwegian University of Science and Technology

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