Ahmad Bagheri

1.8k total citations
66 papers, 1.4k citations indexed

About

Ahmad Bagheri is a scholar working on Control and Systems Engineering, Artificial Intelligence and Mechanical Engineering. According to data from OpenAlex, Ahmad Bagheri has authored 66 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Control and Systems Engineering, 16 papers in Artificial Intelligence and 16 papers in Mechanical Engineering. Recurrent topics in Ahmad Bagheri's work include Robotic Locomotion and Control (13 papers), Adaptive Control of Nonlinear Systems (11 papers) and Metaheuristic Optimization Algorithms Research (9 papers). Ahmad Bagheri is often cited by papers focused on Robotic Locomotion and Control (13 papers), Adaptive Control of Nonlinear Systems (11 papers) and Metaheuristic Optimization Algorithms Research (9 papers). Ahmad Bagheri collaborates with scholars based in Iran, Malaysia and United States. Ahmad Bagheri's co-authors include Saeed Nezamivand Chegini, M. J. Mahmoodabadi, Farid Najafi, Farid Najafi, Mohsen Akbari, N. Nariman-zadeh, Ali Jamali, Nima Amanifard, Behnam Yazdani Bejarbaneh and Salinda Buyamin and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Information Sciences.

In The Last Decade

Ahmad Bagheri

59 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ahmad Bagheri Iran 21 662 451 286 207 169 66 1.4k
Yupu Yang China 22 754 1.1× 656 1.5× 307 1.1× 164 0.8× 261 1.5× 97 1.9k
Mark Schwabacher United States 15 780 1.2× 787 1.7× 179 0.6× 92 0.4× 119 0.7× 45 1.8k
Ramin Rajabioun Türkiye 7 288 0.4× 442 1.0× 116 0.4× 153 0.7× 287 1.7× 13 1.2k
E. Damangir Iran 11 255 0.4× 791 1.8× 372 1.3× 555 2.7× 329 1.9× 12 1.9k
Zhang 15 943 1.4× 126 0.3× 256 0.9× 156 0.8× 150 0.9× 385 1.5k
Guangyu Li China 8 370 0.6× 254 0.6× 202 0.7× 93 0.4× 136 0.8× 24 991
Helon Vicente Hultmann Ayala Brazil 17 389 0.6× 364 0.8× 170 0.6× 158 0.8× 279 1.7× 78 1.1k
Fang Tang China 12 290 0.4× 640 1.4× 129 0.5× 170 0.8× 183 1.1× 36 1.3k
Cláudio M.N.A. Pereira Brazil 21 332 0.5× 233 0.5× 187 0.7× 120 0.6× 83 0.5× 58 1.3k
Sumika Chauhan India 21 417 0.6× 281 0.6× 275 1.0× 88 0.4× 162 1.0× 59 995

Countries citing papers authored by Ahmad Bagheri

Since Specialization
Citations

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

Fields of papers citing papers by Ahmad Bagheri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ahmad Bagheri. 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 Ahmad Bagheri. The network helps show where Ahmad Bagheri may publish in the future.

Co-authorship network of co-authors of Ahmad Bagheri

This figure shows the co-authorship network connecting the top 25 collaborators of Ahmad Bagheri. A scholar is included among the top collaborators of Ahmad Bagheri 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 Ahmad Bagheri. Ahmad Bagheri 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.
Bagheri, Ahmad, et al.. (2020). Optimal design of adaptive and proportional integral derivative controllers using a novel hybrid particle swarm optimization algorithm. Transactions of the Institute of Measurement and Control. 42(8). 1492–1510. 7 indexed citations
2.
Jamali, Ali, et al.. (2020). Multi-objective differential evolution algorithm with fuzzy inference-based adaptive mutation factor for Pareto optimum design of suspension system. Swarm and Evolutionary Computation. 54. 100666–100666. 26 indexed citations
3.
Bagheri, Ahmad, et al.. (2018). Optimal Locations on Timoshenko Beam with PZT S/A for Suppressing 2Dof Vibration Based on LQR-MOPSO. Journal of solid mechanics.. 10(2). 364–386. 6 indexed citations
4.
Bagheri, Ahmad, et al.. (2018). Energy Consumption Analysis for the Limit Cycle Walking Biped Robots. 83. 159–165.
5.
Bagheri, Ahmad, et al.. (2017). Nonlinear Vibration and Stability Analysis of Beam on the Variable Viscoelastic Foundation. Applied and Computational Mechanics. 48(1). 99–110. 4 indexed citations
6.
Bagheri, Ahmad, et al.. (2016). Vibration Attenuation Timoshenko Beam Based on Optimal Placement Sensors/Actuators PZT Patches with LQR-MOPSO. 17(1). 26–60. 6 indexed citations
7.
Bagheri, Ahmad, et al.. (2016). A combined use of adaptive sliding mode control and unscented Kalman filter estimator to improve vehicle yaw stability. Proceedings of the Institution of Mechanical Engineers Part K Journal of Multi-body Dynamics. 231(2). 388–401. 14 indexed citations
8.
Bagheri, Ahmad, et al.. (2014). Stock market forecasting using artificial neural networks. European Online Journal of Natural and Social Sciences. 2. 2404–2411. 3 indexed citations
9.
Mahmoodabadi, M. J., et al.. (2014). HEPSO: High exploration particle swarm optimization. Information Sciences. 273. 101–111. 73 indexed citations
10.
Bagheri, Ahmad, et al.. (2014). Financial forecasting using ANFIS networks with Quantum-behaved Particle Swarm Optimization. Expert Systems with Applications. 41(14). 6235–6250. 143 indexed citations
11.
Mahmoodabadi, M. J., et al.. (2013). Pareto optimum control of a 2-DOF inverted pendulum using approximate feedback linearization and sliding mode control. Transactions of the Institute of Measurement and Control. 36(4). 496–505. 20 indexed citations
12.
Mahmoodabadi, M. J., et al.. (2013). Optimal robust sliding mode tracking control of a biped robot based on ingenious multi-objective PSO. Neurocomputing. 124. 194–209. 57 indexed citations
13.
Mahmoodabadi, M. J., et al.. (2012). Pareto Design of Decoupled Sliding‐Mode Controllers for Nonlinear Systems Based on a Multiobjective Genetic Algorithm. SHILAP Revista de lepidopterología. 2012(1). 19 indexed citations
14.
Mahmoodabadi, M. J., et al.. (2012). Pareto optimal design of the decoupled sliding mode controller for an inverted pendulum system and its stability simulation via Java programming. Mathematical and Computer Modelling. 57(5-6). 1070–1082. 25 indexed citations
15.
Bagheri, Ahmad, et al.. (2011). OPTIMIZATION OF MESHLESS LOCAL PETROV-GALERKIN PARAMETERS USING GENETIC ALGORITHM FOR 3D ELASTO-STATIC PROBLEMS. 24(2). 143–153.
16.
Bagheri, Ahmad, et al.. (2010). Adaptive and Sliding Mode Control for Non- Linear Systems. international journal of advanced design and manufacturing technology. 3(4). 57–62. 4 indexed citations
17.
18.
Bagheri, Ahmad, et al.. (2006). Mathematical simulation of a seven link biped robot on various surfaces and ZMP considerations. Applied Mathematical Modelling. 31(1). 18–37. 29 indexed citations
19.
Bagheri, Ahmad, et al.. (2006). Adaptive neural network control of an underwater remotely operated vehicle (ROV). Annual Conference on Computers. 623–628. 4 indexed citations
20.
Bagheri, Ahmad, et al.. (2005). Determination of kinematic parameters of a passive bipedal walking robot moving on a declined surface by image processing. Journal of Achievements of Materials and Manufacturing Engineering. 16. 136–142. 4 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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