António M. Lopes

7.1k total citations · 1 hit paper
296 papers, 5.3k citations indexed

About

António M. Lopes is a scholar working on Control and Systems Engineering, Modeling and Simulation and Statistical and Nonlinear Physics. According to data from OpenAlex, António M. Lopes has authored 296 papers receiving a total of 5.3k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Control and Systems Engineering, 68 papers in Modeling and Simulation and 52 papers in Statistical and Nonlinear Physics. Recurrent topics in António M. Lopes's work include Fractional Differential Equations Solutions (65 papers), Complex Systems and Time Series Analysis (41 papers) and Advanced Control Systems Design (37 papers). António M. Lopes is often cited by papers focused on Fractional Differential Equations Solutions (65 papers), Complex Systems and Time Series Analysis (41 papers) and Advanced Control Systems Design (37 papers). António M. Lopes collaborates with scholars based in Portugal, China and Iran. António M. Lopes's co-authors include J. A. Tenreiro Machado, Liping Chen, Lucas F. M. da Silva, Dana Copoţ, Clara M. Ionescu, Jason H. T. Bates, Ranchao Wu, María Teresa Restivo, Fernando Gomes de Almeida and Ricardo J. C. Carbas and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Journal of Physical Chemistry B.

In The Last Decade

António M. Lopes

280 papers receiving 5.1k citations

Hit Papers

The role of fractional calculus in modeling biological ph... 2017 2026 2020 2023 2017 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
António M. Lopes Portugal 39 1.4k 1.3k 898 771 593 296 5.3k
Yan Li China 46 1.9k 1.3× 4.1k 3.2× 939 1.0× 2.3k 3.0× 530 0.9× 515 10.6k
Zulqurnain Sabir Pakistan 53 3.1k 2.2× 582 0.5× 972 1.1× 404 0.5× 899 1.5× 282 7.5k
Yonghong Wu China 44 3.0k 2.2× 1.5k 1.2× 1.1k 1.2× 311 0.4× 2.2k 3.8× 490 8.4k
Shantanu Das India 29 1.3k 0.9× 2.0k 1.6× 340 0.4× 671 0.9× 391 0.7× 127 3.7k
Ali Ahmadian Malaysia 46 2.0k 1.4× 586 0.5× 585 0.7× 399 0.5× 558 0.9× 280 6.4k
Jan Awrejcewicz Poland 42 975 0.7× 2.6k 2.1× 2.5k 2.8× 651 0.8× 523 0.9× 747 9.7k
Soheil Salahshour Türkiye 42 2.9k 2.1× 725 0.6× 1.3k 1.4× 287 0.4× 628 1.1× 461 6.3k
Yong Wang China 43 977 0.7× 3.2k 2.5× 366 0.4× 677 0.9× 288 0.5× 321 6.2k
Igor Podlubný Slovakia 30 4.8k 3.4× 6.1k 4.9× 1.4k 1.6× 997 1.3× 1.5k 2.6× 81 9.7k
Praveen Agarwal India 46 3.2k 2.3× 457 0.4× 980 1.1× 283 0.4× 1.6k 2.7× 364 6.9k

Countries citing papers authored by António M. Lopes

Since Specialization
Citations

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

Fields of papers citing papers by António M. Lopes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by António M. Lopes. 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 António M. Lopes. The network helps show where António M. Lopes may publish in the future.

Co-authorship network of co-authors of António M. Lopes

This figure shows the co-authorship network connecting the top 25 collaborators of António M. Lopes. A scholar is included among the top collaborators of António M. Lopes 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 António M. Lopes. António M. Lopes 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.
Wu, Xiaobo, Liping Chen, António M. Lopes, et al.. (2025). Fractional variable-order observer-based method for state-of-charge estimation of lithium-ion batteries. Applied Energy. 389. 125775–125775. 7 indexed citations
2.
Chen, Liping, et al.. (2025). Modeling, analysis and experimental verification of fractional high-order DC-DC converters. Nonlinear Dynamics. 113(25). 34321–34340.
3.
Pereira, Filipe, et al.. (2025). Integration of Deep Learning Vision Systems in Collaborative Robotics for Real-Time Applications. Applied Sciences. 15(3). 1336–1336. 1 indexed citations
4.
Parente, Marco, et al.. (2025). Personalizing Industrial Maintenance Operation Using the Model of Hierarchical Complexity. Journal of Manufacturing and Materials Processing. 9(4). 132–132.
5.
Chen, Liping, et al.. (2024). Adaptive neural network feedback control for uncertain fractional-order building structure vibration systems. Alexandria Engineering Journal. 104. 627–635. 1 indexed citations
6.
Liu, Ping, et al.. (2023). The global dynamics of a new fractional-order chaotic system. Chaos Solitons & Fractals. 175. 114006–114006. 8 indexed citations
7.
Chen, Liping, António M. Lopes, Huafeng Li, et al.. (2023). A new SOH estimation method for Lithium-ion batteries based on model-data-fusion. Energy. 286. 129597–129597. 104 indexed citations
8.
Chen, Liping, et al.. (2023). Adaptive fractional-order genetic-particle swarm optimization Otsu algorithm for image segmentation. Applied Intelligence. 53(22). 26949–26966. 17 indexed citations
9.
Hendy, Ahmed S., et al.. (2023). A Matrix Transform Technique for Distributed-Order Time-Fractional Advection–Dispersion Problems. Fractal and Fractional. 7(9). 649–649. 1 indexed citations
10.
Bao, Xinyuan, Liping Chen, António M. Lopes, et al.. (2023). Hybrid deep neural network with dimension attention for state-of-health estimation of Lithium-ion Batteries. Energy. 278. 127734–127734. 70 indexed citations
11.
Moghaddam, Behrouz Parsa, et al.. (2023). A Numerical Algorithm for Solving Nonlocal Nonlinear Stochastic Delayed Systems with Variable-Order Fractional Brownian Noise. Fractal and Fractional. 7(4). 293–293. 9 indexed citations
12.
Liu, Yang, et al.. (2023). Theoretical analysis and experimental verification of fractional-order RC cobweb circuit network. Chaos Solitons & Fractals. 172. 113541–113541. 3 indexed citations
13.
Chen, Liping, et al.. (2023). A variable fractional-order sliding mode controller for uncertain vibration building structures. Structures. 55. 2023–2035. 3 indexed citations
14.
Fardi, Mojtaba, et al.. (2023). Inclusion Properties of p-Valent Functions Associated with Borel Distribution Functions. Mathematics. 11(16). 3511–3511. 3 indexed citations
15.
Khodabin, M., et al.. (2022). A New Approach to Approximate Solutions of Single Time-Delayed Stochastic Integral Equations via Orthogonal Functions. Symmetry. 14(10). 2085–2085. 2 indexed citations
16.
Beygi, Reza, et al.. (2022). Intelligence, Beliefs on IQ and Learning Style predict Academic Performance in Mechanical Engineering Students. SHILAP Revista de lepidopterología. 8(1). 59–72. 4 indexed citations
17.
Machado, J. A. Tenreiro, et al.. (2021). Overview in Summabilities: Summation Methods for Divergent Series, Ramanujan Summation and Fractional Finite Sums. Mathematics. 9(22). 2963–2963. 3 indexed citations
18.
Moghaddam, Behrouz Parsa, et al.. (2019). Computational scheme for solving nonlinear fractional stochastic differential equations with delay. Stochastic Analysis and Applications. 37(6). 893–908. 38 indexed citations
19.
Chen, Liping, Tingwen Huang, J. A. Tenreiro Machado, et al.. (2019). Delay-dependent criterion for asymptotic stability of a class of fractional-order memristive neural networks with time-varying delays. Neural Networks. 118. 289–299. 74 indexed citations
20.
Lopes, António M.. (2009). Activos intangibles y la realidad objetiva patrimonial. 139–159. 1 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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