Fernando Fausto

1.3k total citations · 1 hit paper
17 papers, 825 citations indexed

About

Fernando Fausto is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Fernando Fausto has authored 17 papers receiving a total of 825 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 5 papers in Computer Vision and Pattern Recognition and 3 papers in Computational Theory and Mathematics. Recurrent topics in Fernando Fausto's work include Metaheuristic Optimization Algorithms Research (9 papers), Evolutionary Algorithms and Applications (7 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). Fernando Fausto is often cited by papers focused on Metaheuristic Optimization Algorithms Research (9 papers), Evolutionary Algorithms and Applications (7 papers) and Advanced Multi-Objective Optimization Algorithms (3 papers). Fernando Fausto collaborates with scholars based in Mexico, India and Germany. Fernando Fausto's co-authors include Erik Cuevas, Daniel Zaldívar, Bernardo Morales-Castañeda, Adrián González, Alma Rodríguez, Marco Pérez‐Cisneros, Arturo Valdivia, Ángel G. Andrade, Ram Sarkar and Raúl Rojas and has published in prestigious journals such as Applied Soft Computing, Knowledge-Based Systems and Energies.

In The Last Decade

Fernando Fausto

17 papers receiving 800 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

A better balance in metaheuristic algorithms: Does it exist?

2020 283 citations Bernardo Morales-Castañeda, Daniel Zaldívar et al. Swarm and Evolutionary Computation profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Fernando Fausto Mexico	12	490	242	133	127	92	17	825
Hassan Shaban Egypt	10	564 1.2×	221 0.9×	194 1.5×	175 1.4×	96 1.0×	19	1.0k
Nabil Neggaz Algeria	14	590 1.2×	201 0.8×	205 1.5×	89 0.7×	79 0.9×	24	971
Ahmad Nickabadi Iran	9	503 1.0×	205 0.8×	191 1.4×	128 1.0×	162 1.8×	31	906
Sukanta Nama India	20	653 1.3×	372 1.5×	98 0.7×	92 0.7×	90 1.0×	26	901
Xing Cai China	6	326 0.7×	141 0.6×	98 0.7×	116 0.9×	173 1.9×	6	769
Seyed Hamid Zahiri Iran	17	416 0.8×	145 0.6×	119 0.9×	177 1.4×	106 1.2×	81	865
Yiying Zhang China	16	686 1.4×	263 1.1×	107 0.8×	228 1.8×	158 1.7×	23	1.1k
Honghua Rao China	12	368 0.8×	190 0.8×	105 0.8×	81 0.6×	89 1.0×	19	624
Xinming Zhang China	12	409 0.8×	169 0.7×	119 0.9×	71 0.6×	180 2.0×	33	686

Countries citing papers authored by Fernando Fausto

Since Specialization

Citations

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

Fields of papers citing papers by Fernando Fausto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fernando Fausto

This figure shows the co-authorship network connecting the top 25 collaborators of Fernando Fausto. A scholar is included among the top collaborators of Fernando Fausto 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 Fernando Fausto. Fernando Fausto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

González, Adrián, et al.. (2024). Detection of COVID-19: A Metaheuristic-Optimized Maximally Stable Extremal Regions Approach. Symmetry. 16(7). 870–870. 1 indexed citations

Fausto, Fernando, et al.. (2021). Inverse Optimal Control Using Metaheuristics of Hydropower Plant Model via Forecasting Based on the Feature Engineering. Energies. 14(21). 7356–7356. 5 indexed citations

Morales-Castañeda, Bernardo, Daniel Zaldívar, Erik Cuevas, Fernando Fausto, & Alma Rodríguez. (2020). A better balance in metaheuristic algorithms: Does it exist?. Swarm and Evolutionary Computation. 54. 100671–100671. 283 indexed citations breakdown →

Cuevas, Erik, et al.. (2020). Moth Swarm Algorithm for Image Contrast Enhancement. Knowledge-Based Systems. 212. 106607–106607. 34 indexed citations

Morales-Castañeda, Bernardo, et al.. (2019). An improved Simulated Annealing algorithm based on ancient metallurgy techniques. Applied Soft Computing. 84. 105761–105761. 43 indexed citations

Cuevas, Erik, Fernando Fausto, & Adrián González. (2019). New Advancements in Swarm Algorithms: Operators and Applications. Intelligent systems reference library. 56 indexed citations

Fausto, Fernando, et al.. (2019). A Real-Coded Optimal Sensor Deployment Scheme for Wireless Sensor Networks Based on the Social Spider Optimization Algorithm. International Journal of Computational Intelligence Systems. 12(2). 676–676. 2 indexed citations

Fausto, Fernando, et al.. (2019). From ants to whales: metaheuristics for all tastes. Artificial Intelligence Review. 53(1). 753–810. 138 indexed citations

Cuevas, Erik, et al.. (2018). Ls-II: An Improved Locust Search Algorithm for Solving Optimization Problems. Mathematical Problems in Engineering. 2018. 1–15. 11 indexed citations

10.

Cuevas, Erik, et al.. (2018). Social Spider Optimization Algorithm: Modifications, Applications, and Perspectives. Mathematical Problems in Engineering. 2018. 1–29. 48 indexed citations

11.

Fausto, Fernando, Erik Cuevas, Arturo Valdivia, & Adrián González. (2017). A global optimization algorithm inspired in the behavior of selfish herds. Biosystems. 160. 39–55. 111 indexed citations

12.

Fausto, Fernando, et al.. (2017). A new descriptor for image matching based on bionic principles. Pattern Analysis and Applications. 20(4). 1245–1259. 25 indexed citations

13.

Valdivia, Arturo, et al.. (2017). A States of Matter Search-Based Approach for Solving the Problem of Intelligent Power Allocation in Plug-in Hybrid Electric Vehicles. Energies. 10(1). 92–92. 11 indexed citations

14.

González, Adrián, Erik Cuevas, Fernando Fausto, Arturo Valdivia, & Raúl Rojas. (2017). A template matching approach based on the behavior of swarms of locust. Applied Intelligence. 47(4). 1087–1098. 9 indexed citations

15.

Valdivia, Arturo, Daniel Zaldívar, Erik Cuevas, et al.. (2017). A Chaos-Embedded Gravitational Search Algorithm for the Identification of Electrical Parameters of Photovoltaic Cells. Energies. 10(7). 1052–1052. 19 indexed citations

16.

Fausto, Fernando, Erik Cuevas, & Marco Pérez‐Cisneros. (2016). An Optimization Based Approach for Maximizing the Information Content of Keypoints Detected on a Digital Image. 1–5. 4 indexed citations

17.

Cuevas, Erik, Adrián González, Fernando Fausto, Daniel Zaldívar, & Marco Pérez‐Cisneros. (2015). Multithreshold Segmentation by Using an Algorithm Based on the Behavior of Locust Swarms. Mathematical Problems in Engineering. 2015. 1–25. 25 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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