Éric Lefèvre

1.7k total citations
47 papers, 928 citations indexed

About

Éric Lefèvre is a scholar working on Artificial Intelligence, Management Science and Operations Research and Control and Systems Engineering. According to data from OpenAlex, Éric Lefèvre has authored 47 papers receiving a total of 928 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 13 papers in Management Science and Operations Research and 10 papers in Control and Systems Engineering. Recurrent topics in Éric Lefèvre's work include Multi-Criteria Decision Making (12 papers), Bayesian Modeling and Causal Inference (9 papers) and Rough Sets and Fuzzy Logic (9 papers). Éric Lefèvre is often cited by papers focused on Multi-Criteria Decision Making (12 papers), Bayesian Modeling and Causal Inference (9 papers) and Rough Sets and Fuzzy Logic (9 papers). Éric Lefèvre collaborates with scholars based in France and Tunisia. Éric Lefèvre's co-authors include P. Vannoorenberghe, Olivier Colot, Zied Elouedi, David Mercier, Raphaël Romary, Rémus Pusca, François Delmotte, Nour‐Eddin El Faouzi, Cristian Demian and Daniel Jolly and has published in prestigious journals such as IEEE Transactions on Industrial Electronics, Expert Systems with Applications and IEEE Transactions on Industry Applications.

In The Last Decade

Éric Lefèvre

43 papers receiving 877 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Éric Lefèvre France 15 439 256 211 157 122 47 928
Antonio Rodríguez-Díaz Mexico 15 792 1.8× 204 0.8× 307 1.5× 341 2.2× 82 0.7× 46 1.5k
Mahdi Imani United States 21 314 0.7× 165 0.6× 317 1.5× 205 1.3× 89 0.7× 68 1.2k
Anna Maria Fanelli Italy 18 788 1.8× 164 0.6× 133 0.6× 169 1.1× 64 0.5× 101 1.2k
Xinwei Cao China 20 480 1.1× 183 0.7× 413 2.0× 118 0.8× 122 1.0× 38 1.2k
Julien Lepagnot France 9 679 1.5× 97 0.4× 158 0.7× 387 2.5× 175 1.4× 36 1.4k
Xiaoan Tang China 15 207 0.5× 257 1.0× 223 1.1× 113 0.7× 101 0.8× 59 819
Ilhem Boussaïd Algeria 4 680 1.5× 77 0.3× 150 0.7× 398 2.5× 182 1.5× 4 1.3k
Simon Coupland United Kingdom 24 1.5k 3.4× 641 2.5× 278 1.3× 282 1.8× 84 0.7× 65 1.9k
Ender Sevinç Türkiye 8 488 1.1× 65 0.3× 89 0.4× 203 1.3× 110 0.9× 18 946

Countries citing papers authored by Éric Lefèvre

Since Specialization
Citations

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

Fields of papers citing papers by Éric Lefèvre

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Éric Lefèvre

This figure shows the co-authorship network connecting the top 25 collaborators of Éric Lefèvre. A scholar is included among the top collaborators of Éric Lefèvre 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 Éric Lefèvre. Éric Lefèvre 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.
Elouedi, Zied, et al.. (2023). Re-sampling of multi-class imbalanced data using belief function theory and ensemble learning. International Journal of Approximate Reasoning. 156. 1–15. 14 indexed citations
2.
Lefèvre, Éric, et al.. (2023). Optimization problems with evidential linear objective. International Journal of Approximate Reasoning. 161. 108987–108987.
3.
Elouedi, Zied, et al.. (2023). An ensemble classifier through rough set reducts for handling data with evidential attributes. Information Sciences. 635. 414–429. 10 indexed citations
4.
Elouedi, Zied, et al.. (2021). CIMMEP: constrained integrated method for CBR maintenance based on evidential policies. Applied Intelligence. 52(6). 6939–6954. 1 indexed citations
5.
Pusca, Rémus, et al.. (2020). Adapted Coil Sensors for Measuring the External Magnetic Field of Electrical Machines. HAL (Le Centre pour la Communication Scientifique Directe). 1–7. 3 indexed citations
6.
Pusca, Rémus, et al.. (2019). Detection of the Stator Winding Inter-Turn Faults in Asynchronous and Synchronous Machines Through the Correlation Between Harmonics of the Voltage of Two Magnetic Flux Sensors. IEEE Transactions on Industry Applications. 55(3). 2682–2689. 44 indexed citations
7.
Elouedi, Zied, et al.. (2019). An evidential integrated method for maintaining case base and vocabulary containers within CBR systems. Information Sciences. 529. 214–229. 4 indexed citations
8.
Porumbel, Daniel Cosmin, et al.. (2018). The capacitated vehicle routing problem with evidential demands. International Journal of Approximate Reasoning. 95. 124–151. 15 indexed citations
9.
Mercier, David, et al.. (2017). Face pixel detection using evidential calibration and fusion. International Journal of Approximate Reasoning. 91. 202–215. 9 indexed citations
10.
Pusca, Rémus, et al.. (2017). Diagnosis of induction machines using external magnetic field and correlation coefficient. 531–536. 8 indexed citations
11.
Mercier, David, et al.. (2017). Information fusion of external flux sensors for detection of inter-turn short circuit faults in induction machines. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. 8076–8081. 7 indexed citations
12.
Mercier, David, et al.. (2015). Proposition and learning of some belief function contextual correction mechanisms. International Journal of Approximate Reasoning. 72. 4–42. 19 indexed citations
13.
Samet, Ahmed, Éric Lefèvre, & Sadok Ben Yahia. (2014). Integration of Extra-Information for Belief Function Theory Conflict Management Problem Through Generic Association Rules. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems. 22(4). 531–551. 2 indexed citations
14.
Elouedi, Zied, et al.. (2014). Multi-Criteria Decision Making Method with Belief Preference Relations. International Journal of Uncertainty Fuzziness and Knowledge-Based Systems. 22(4). 573–590.
15.
Mercier, David, Éric Lefèvre, & François Delmotte. (2011). Belief functions contextual discounting and canonical decompositions. International Journal of Approximate Reasoning. 53(2). 146–158. 29 indexed citations
16.
Lefèvre, Éric, et al.. (2011). Evidential calibration process of multi-agent based system: An application to forensic entomology. Expert Systems with Applications. 39(3). 2361–2374. 7 indexed citations
17.
Lefèvre, Éric, et al.. (2006). Improvement of an association algorithm for obstacle tracking. Information Fusion. 9(2). 234–245. 6 indexed citations
18.
Lefèvre, Éric, Olivier Colot, & P. Vannoorenberghe. (2003). Reply to the Comments of R. Haenni on the paper “Belief functions combination and conflict management”. Information Fusion. 4(1). 63–65. 6 indexed citations
19.
Lefèvre, Éric, et al.. (2000). A generic framework for resolving the conflict in the combination of belief structures. MOD4/11–MOD4/18 vol.1. 26 indexed citations
20.
Lefèvre, Éric, P. Vannoorenberghe, & Olivier Colot. (1999). Using information criteria in Dempster-Shafer's basic belief assignment. 1496. 173–178 vol.1. 7 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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