Éric Lefèvre

1.7k citations
47 papers · 928 indexed · h-index 15

Impact in

Papers in

Éric Lefèvre

43 papers receiving 877 citations

Peers

Éric Lefèvre
Comparison fields: 5 of 101
  • Management Science and Operations Research 256
  • Artificial Intelligence 439
  • Computational Theory and Mathematics 157
  • Control and Systems Engineering 211
  • Statistics, Probability and Uncertainty 53
Replace Shi Wen-kang with:
Shi Wen-kang China
Zhu Zhen-fu China
Mahdi Imani United States
Mingli Song China
C.M.H. Kuijpers Spain
Xiaoan Tang China
Antonio Rodríguez-Díaz Mexico
Honghui Xu United States
Mario Andrés Muñoz Australia
Éric Lefèvre relative to Shi Wen-kang China Shi Wen-kang's profile →
Citations per field
00.5×1.5×2.1×
Shi Wen-kang · 1×
Citations per year

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-authors

The 22 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.

Border = papers with Éric Lefèvre Line = papers co-authored together Éric Lefèvre links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002346
2 201772
3 201371
4 201860
5 201944
6 201129
7 200629
8 200026
9 200924
10 201820
11 201519
12 201416
13 201815
14 202314
15 201114
16 202310
17 201610
18 20179
19 20178
20 20218

About Éric Lefèvre

Éric Lefèvre is a scholar working on Artificial Intelligence, Management Science and Operations Research, Control and Systems Engineering, Computational Theory and Mathematics and Mechanical Engineering, having authored 47 papers that have together received 928 indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (12 papers), Bayesian Modeling and Causal Inference (9 papers), Rough Sets and Fuzzy Logic (9 papers), Non-Destructive Testing Techniques (6 papers), Fault Detection and Control Systems (6 papers), Machine Fault Diagnosis Techniques (6 papers), Imbalanced Data Classification Techniques (4 papers) and Data Mining Algorithms and Applications (4 papers). The work is most often cited by research in Management Science and Operations Research (256 citations), Artificial Intelligence (439 citations), Computational Theory and Mathematics (157 citations), Control and Systems Engineering (211 citations) and Statistics, Probability and Uncertainty (53 citations). Éric Lefèvre has collaborated with scholars based in France and Tunisia. Frequent co-authors include Olivier Colot, P. Vannoorenberghe, Zied Elouedi, David Mercier, Raphaël Romary, Rémus Pusca, François Delmotte, Nour‐Eddin El Faouzi, Cristian Demian and Daniel Jolly. Their work appears in journals such as International Journal of Approximate Reasoning, Information Fusion, Information Sciences, Soft Computing 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.

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