Alexander Gegov

2.8k total citations
136 papers, 1.3k citations indexed

About

Alexander Gegov is a scholar working on Artificial Intelligence, Control and Systems Engineering and Management Science and Operations Research. According to data from OpenAlex, Alexander Gegov has authored 136 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Artificial Intelligence, 38 papers in Control and Systems Engineering and 28 papers in Management Science and Operations Research. Recurrent topics in Alexander Gegov's work include Fuzzy Logic and Control Systems (44 papers), Multi-Criteria Decision Making (26 papers) and Neural Networks and Applications (26 papers). Alexander Gegov is often cited by papers focused on Fuzzy Logic and Control Systems (44 papers), Multi-Criteria Decision Making (26 papers) and Neural Networks and Applications (26 papers). Alexander Gegov collaborates with scholars based in United Kingdom, Bulgaria and Mexico. Alexander Gegov's co-authors include Mihaela Cocea, Han Liu, David Sanders, Raheleh Jafari, Sina Razvarz, Bhagawati Prasad Joshi, Paul M. Frank, Han Liu, Jasper Graham‐Jones and Mo Adda and has published in prestigious journals such as European Journal of Operational Research, IEEE Access and IEEE Transactions on Fuzzy Systems.

In The Last Decade

Alexander Gegov

121 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Alexander Gegov United Kingdom 19 521 462 345 198 189 136 1.3k
Antonio González Spain 22 935 1.8× 489 1.1× 355 1.0× 206 1.0× 398 2.1× 89 1.7k
Piero P. Bonissone United States 24 1.1k 2.1× 527 1.1× 454 1.3× 374 1.9× 169 0.9× 112 2.1k
Jorge Casillas Spain 25 1.6k 3.1× 299 0.6× 259 0.8× 210 1.1× 232 1.2× 78 2.4k
Sujit Das India 15 277 0.5× 630 1.4× 234 0.7× 268 1.4× 161 0.9× 46 1.1k
Philippe Fortemps Belgium 21 386 0.7× 814 1.8× 468 1.4× 339 1.7× 301 1.6× 40 1.8k
Rami Al‐Hmouz Saudi Arabia 19 583 1.1× 475 1.0× 138 0.4× 366 1.8× 64 0.3× 70 1.3k
Hideki Katagiri Japan 21 244 0.5× 653 1.4× 556 1.6× 192 1.0× 500 2.6× 160 1.5k
László T. Kóczy Hungary 21 1.7k 3.3× 621 1.3× 463 1.3× 508 2.6× 303 1.6× 262 2.5k
Anna Maria Fanelli Italy 18 788 1.5× 164 0.4× 133 0.4× 169 0.9× 66 0.3× 101 1.2k
Rafael Alcalá Spain 25 2.3k 4.4× 384 0.8× 308 0.9× 515 2.6× 247 1.3× 71 2.9k

Countries citing papers authored by Alexander Gegov

Since Specialization
Citations

This map shows the geographic impact of Alexander Gegov's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Alexander Gegov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexander Gegov more than expected).

Fields of papers citing papers by Alexander Gegov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alexander Gegov. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Alexander Gegov. The network helps show where Alexander Gegov may publish in the future.

Co-authorship network of co-authors of Alexander Gegov

This figure shows the co-authorship network connecting the top 25 collaborators of Alexander Gegov. A scholar is included among the top collaborators of Alexander Gegov based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alexander Gegov. Alexander Gegov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Gegov, Alexander, et al.. (2025). Data-Driven Predictive Modelling of Agile Projects Using Explainable Artificial Intelligence. Electronics. 14(13). 2609–2609. 1 indexed citations
2.
Gegov, Alexander, et al.. (2025). Heuristic Fuzzy Approach to Traffic Flow Modelling and Control on Urban Networks. Future Internet. 17(5). 227–227. 1 indexed citations
3.
Taheri, Rahim, et al.. (2024). Unveiling vulnerabilities in deep learning-based malware detection: Differential privacy driven adversarial attacks. Computers & Security. 146. 104035–104035. 19 indexed citations
4.
5.
Penev, Kalin, et al.. (2024). Energy Efficiency Evaluation of Artificial Intelligence Algorithms. Electronics. 13(19). 3836–3836. 2 indexed citations
6.
Gegov, Alexander, et al.. (2023). The Application of Z-Numbers in Fuzzy Decision Making: The State of the Art. Information. 14(7). 400–400. 17 indexed citations
7.
Gegov, Alexander, et al.. (2023). Large-Scale Group Decision-Making Method Using Hesitant Fuzzy Rule-Based Network for Asset Allocation. Information. 14(11). 588–588.
8.
9.
Gegov, Alexander, et al.. (2023). Fuzzy Networks for Explainable Artificial Intelligence. TU/e Research Portal. 199–200. 1 indexed citations
10.
Gegov, Alexander, et al.. (2023). Modelling and Simulation of Traffic Light Control. Cybernetics and Information Technologies. 23(3). 179–191. 1 indexed citations
11.
Joshi, Bhagawati Prasad, Navneet Joshi, & Alexander Gegov. (2023). TOPSIS based Renewable-Energy-Source-Selection using Moderator Intuitionistic Fuzzy Set. International Journal of Mathematical Engineering and Management Sciences. 8(5). 979–990. 11 indexed citations
12.
Jafari, Raheleh, et al.. (2022). Pipeline Leak Detection and Estimation Using Fuzzy PID Observer. Electronics. 11(1). 152–152. 1 indexed citations
13.
Hopgood, Adrian A., et al.. (2022). Deep Learning Models for the Diagnosis and Screening of COVID-19: A Systematic Review. SN Computer Science. 3(5). 397–397. 13 indexed citations
14.
Razvarz, Sina, et al.. (2019). Leakage Detection in Pipeline Based on Second Order Extended Kalman Filter Observer. IFAC-PapersOnLine. 52(29). 116–121. 6 indexed citations
15.
Liu, Han, Alexander Gegov, & Frederic Stahl. (2013). J-measure based hybrid pruning for complexity reduction in classification rules. CentAUR (University of Reading). 12(9). 443–446. 7 indexed citations
16.
Gegov, Alexander, et al.. (2010). Implementation of a fuzzy model for computation of margins in cancer treatment.
17.
Gegov, Alexander, et al.. (2009). Model optimisation for complex systems using fuzzy networks theory. International Conference on Artificial Intelligence. 116–121. 2 indexed citations
18.
Gegov, Alexander. (2009). Complex systems modelling by rule based networks. International Conference on Artificial Intelligence. 122–127. 2 indexed citations
19.
Gegov, Alexander, et al.. (2007). Advanced Inference in Fuzzy Systems by Rule Base Compression.. European Society for Fuzzy Logic and Technology Conference. 14(3). 111–118. 5 indexed citations
20.
Gegov, Alexander. (2007). Complexity Management in Fuzzy Systems: A Rule Base Compression Approach (Studies in Fuzziness and Soft Computing). Springer eBooks. 24 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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