Éric Lefèvre
Impact in
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- Multi-Criteria Decision Making
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- Machine Fault Diagnosis Techniques
Papers in
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- Multi-Criteria Decision Making 46
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- Bayesian Modeling and Causal Inference 12
- Imbalanced Data Classification Techniques 10
- AI-based Problem Solving and Planning 9
- Co-authors
- Zied Elouedi (59 shared papers)Olivier Colot (4 shared papers)P. Vannoorenberghe (4 shared papers)David Mercier (38 shared papers)Rémus Pusca (12 shared papers)Raphaël Romary (12 shared papers)François Delmotte (11 shared papers)Frédéric Pichon (17 shared papers)
In The Last Decade
Éric Lefèvre
114 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 77
- Management Science and Operations Research 577
- Control and Systems Engineering 253
- Artificial Intelligence 295
- Computational Theory and Mathematics 98
- Information Systems 122
Countries citing papers authored by Éric Lefèvre
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
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-authors
The 19 scholars most cited alongside Éric Lefèvre, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 120 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 378 | |
| 2 | 2013 | 94 | |
| 3 | 2017 | 78 | |
| 4 | 2018 | 66 | |
| 5 | 2019 | 51 | |
| 6 | 2011 | 42 | |
| 7 | 2006 | 33 | |
| 8 | 2009 | 31 | |
| 9 | 2000 | 26 | |
| 10 | 2015 | 26 | |
| 11 | 2011 | 23 | |
| 12 | 2018 | 23 | |
| 13 | 2018 | 21 | |
| 14 | 2023 | 17 | |
| 15 | 2014 | 16 | |
| 16 | 2010 | 15 | |
| 17 | 2016 | 15 | |
| 18 | 2012 | 14 | |
| 19 | 2023 | 14 | |
| 20 | 2017 | 13 |
About Éric Lefèvre
Éric Lefèvre is a scholar working on Management Science and Operations Research, Artificial Intelligence, Computational Theory and Mathematics, Information Systems and Control and Systems Engineering, having authored 120 papers that have together received 1.4k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (46 papers), Rough Sets and Fuzzy Logic (16 papers), Machine Fault Diagnosis Techniques (13 papers), Bayesian Modeling and Causal Inference (12 papers), Imbalanced Data Classification Techniques (10 papers), AI-based Problem Solving and Planning (9 papers), Spam and Phishing Detection (8 papers) and Complex Network Analysis Techniques (7 papers). The work is most often cited by research in Management Science and Operations Research (577 citations), Control and Systems Engineering (253 citations), Artificial Intelligence (295 citations), Computational Theory and Mathematics (98 citations) and Information Systems (122 citations). Éric Lefèvre has collaborated with scholars based in France and Tunisia. Frequent co-authors include Zied Elouedi, Olivier Colot, P. Vannoorenberghe, David Mercier, Rémus Pusca, Raphaël Romary, François Delmotte, Frédéric Pichon, Ahmed Samet and Nour‐Eddin El Faouzi. Their work appears in journals such as International Journal of Approximate Reasoning, Lecture notes in computer science, Information Fusion, Information Sciences and International Journal of Uncertainty Fuzziness and Knowledge-Based Systems.
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.