Mohammad El-Bardini

1.0k total citations
51 papers, 791 citations indexed

About

Mohammad El-Bardini is a scholar working on Artificial Intelligence, Control and Systems Engineering and Computational Theory and Mathematics. According to data from OpenAlex, Mohammad El-Bardini has authored 51 papers receiving a total of 791 indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Artificial Intelligence, 32 papers in Control and Systems Engineering and 10 papers in Computational Theory and Mathematics. Recurrent topics in Mohammad El-Bardini's work include Fuzzy Logic and Control Systems (26 papers), Neural Networks and Applications (17 papers) and Advanced Control Systems Design (10 papers). Mohammad El-Bardini is often cited by papers focused on Fuzzy Logic and Control Systems (26 papers), Neural Networks and Applications (17 papers) and Advanced Control Systems Design (10 papers). Mohammad El-Bardini collaborates with scholars based in Egypt, Colombia and United Arab Emirates. Mohammad El-Bardini's co-authors include Ahmad M. El-Nagar, Nabila M. El-Rabaie, A. Zaki, Mohamed A. El-Brawany, M. A. Fkirin and Gamal Attiya and has published in prestigious journals such as Expert Systems with Applications, IEEE Transactions on Fuzzy Systems and Journal of the Franklin Institute.

In The Last Decade

Mohammad El-Bardini

49 papers receiving 766 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mohammad El-Bardini Egypt 19 512 454 109 89 84 51 791
Ahmad M. El-Nagar Egypt 19 501 1.0× 506 1.1× 91 0.8× 92 1.0× 90 1.1× 46 806
Agustín Jiménez Spain 14 273 0.5× 269 0.6× 90 0.8× 78 0.9× 75 0.9× 53 622
Víctor Costa da Silva Campos Brazil 11 426 0.8× 230 0.5× 75 0.7× 76 0.9× 156 1.9× 27 668
Müjde Güzelkaya Türkiye 18 1.0k 2.0× 509 1.1× 285 2.6× 42 0.5× 43 0.5× 88 1.3k
Chang Sun China 5 234 0.5× 491 1.1× 74 0.7× 43 0.5× 24 0.3× 8 755
Junhong Nie Singapore 13 287 0.6× 439 1.0× 156 1.4× 29 0.3× 151 1.8× 33 754
Yanling Wei China 11 651 1.3× 161 0.4× 108 1.0× 81 0.9× 399 4.8× 19 939
Chia-Hung Hsu Taiwan 8 257 0.5× 346 0.8× 77 0.7× 38 0.4× 42 0.5× 14 575
Bruno Sielly Jales Costa Brazil 12 295 0.6× 385 0.8× 60 0.6× 27 0.3× 72 0.9× 27 644
Ye Wang China 17 915 1.8× 200 0.4× 101 0.9× 27 0.3× 128 1.5× 68 1.1k

Countries citing papers authored by Mohammad El-Bardini

Since Specialization
Citations

This map shows the geographic impact of Mohammad El-Bardini'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 Mohammad El-Bardini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad El-Bardini more than expected).

Fields of papers citing papers by Mohammad El-Bardini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad El-Bardini. 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 Mohammad El-Bardini. The network helps show where Mohammad El-Bardini may publish in the future.

Co-authorship network of co-authors of Mohammad El-Bardini

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad El-Bardini. A scholar is included among the top collaborators of Mohammad El-Bardini 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 Mohammad El-Bardini. Mohammad El-Bardini 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.
El-Nagar, Ahmad M., et al.. (2025). An embedded deep learning neural network control for a wheeled mobile robot. Robotics and Autonomous Systems. 194. 105154–105154.
2.
El-Bardini, Mohammad, et al.. (2025). Probabilistic fuzzy neural network-based indirect adaptive control framework for dynamic systems. ISA Transactions. 166. 179–195.
3.
El-Bardini, Mohammad, et al.. (2025). Deep reinforcement learning-based adaptive fuzzy control for electro-hydraulic servo system. Neural Computing and Applications. 37(30). 24607–24624. 2 indexed citations
4.
El-Nagar, Ahmad M., et al.. (2023). Recurrent general type-2 fuzzy neural networks for nonlinear dynamic systems identification. ISA Transactions. 140. 170–182. 5 indexed citations
5.
El-Bardini, Mohammad, et al.. (2023). Real time adaptive PID controller based on quantum neural network for nonlinear systems. Engineering Applications of Artificial Intelligence. 126. 106952–106952. 15 indexed citations
6.
El-Bardini, Mohammad, et al.. (2023). Embedded adaptive fractional-order sliding mode control based on TSK fuzzy system for nonlinear fractional-order systems. Soft Computing. 27(21). 15463–15477. 3 indexed citations
7.
El-Nagar, Ahmad M., et al.. (2022). Hybrid deep learning controller for nonlinear systems based on adaptive learning rates. International Journal of Control. 96(7). 1710–1723. 2 indexed citations
8.
El-Nagar, Ahmad M., et al.. (2022). Polynomial Recurrent Neural Network-Based Adaptive PID Controller With Stable Learning Algorithm. Neural Processing Letters. 55(3). 2885–2910. 6 indexed citations
9.
El-Nagar, Ahmad M., et al.. (2021). Embedded Fuzzy PD Controller for Robot Manipulator. 1–6. 4 indexed citations
10.
El-Nagar, Ahmad M., et al.. (2021). Adaptive interval type-2 fuzzy controller for nonlinear networked Wiener systems subject to packet dropout and time-varying delay. ISA Transactions. 128(Pt A). 565–580. 8 indexed citations
11.
El-Nagar, Ahmad M., et al.. (2020). Diagonal recurrent neural network observer-based adaptive control for unknown nonlinear systems. Transactions of the Institute of Measurement and Control. 42(15). 2833–2856. 6 indexed citations
12.
Zaki, A., et al.. (2020). Deep learning controller for nonlinear system based on Lyapunov stability criterion. Neural Computing and Applications. 33(5). 1515–1531. 22 indexed citations
13.
El-Nagar, Ahmad M., et al.. (2020). Embedded fuzzy sliding mode control for polymer extrusion process. ISA Transactions. 103. 237–251. 7 indexed citations
14.
El-Nagar, Ahmad M., et al.. (2019). A novel fuzzy Wiener-based nonlinear modelling for engineering applications. ISA Transactions. 97. 130–142. 26 indexed citations
15.
El-Nagar, Ahmad M., et al.. (2019). Stable adaptive probabilistic Takagi–Sugeno–Kang fuzzy controller for dynamic systems with uncertainties. ISA Transactions. 98. 271–283. 21 indexed citations
16.
El-Nagar, Ahmad M., et al.. (2018). Model Predictive Control Based on Modified Smith Predictor for Networked Control Systems. 27(2). 237–258. 2 indexed citations
17.
El-Nagar, Ahmad M., et al.. (2016). Fuzzy smith predictor for networked control systems. 39. 437–443. 1 indexed citations
18.
El-Nagar, Ahmad M. & Mohammad El-Bardini. (2015). Hardware-in-the-loop simulation of interval type-2 fuzzy PD controller for uncertain nonlinear system using low cost microcontroller. Applied Mathematical Modelling. 40(3). 2346–2355. 21 indexed citations
19.
El-Bardini, Mohammad & Ahmad M. El-Nagar. (2014). Interval type-2 fuzzy PID controller for uncertain nonlinear inverted pendulum system. ISA Transactions. 53(3). 732–743. 108 indexed citations
20.
El-Nagar, Ahmad M. & Mohammad El-Bardini. (2014). Interval type-2 fuzzy neural network controller for a multivariable anesthesia system based on a hardware-in-the-loop simulation. Artificial Intelligence in Medicine. 61(1). 1–10. 16 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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