Inés Couso

106 papers receiving 1.9k citations

Peers

Inés Couso
Comparison fields: 5 of 122
  • Statistics and Probability 791
  • Management Science and Operations Research 910
  • Artificial Intelligence 1.2k
  • General Decision Sciences 52
  • Computational Theory and Mathematics 436
Replace Rafik Aziz Aliev with:
Rafik Aziz Aliev Azerbaijan
Toshiaki Murofushi Japan
Serafı́n Moral Spain
Lev V. Utkin Russia
Robert Kennes Belgium
Anne-Laure Jousselme Canada
Jonathan Lawry United Kingdom
Éloi Bossé Canada
Antonio González Spain
Gilles Mauris France
Inés Couso relative to Rafik Aziz Aliev Azerbaijan Rafik Aziz Aliev's profile →
Citations per field
00.5×1.5×1.8×
Rafik Aziz Aliev · 1×
Citations per year

Countries citing papers authored by Inés Couso

Since Specialization
Citations

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

Fields of papers citing papers by Inés Couso

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Inés Couso, 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 Inés Couso Line = papers co-authored together Inés Couso links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20251
3 20251
4 20242
5 201713
6 20173
7 20151
8 201422
9 20141
10 201463
11 20144
12 201116
13 201130
14
A baseline learning genetic fuzzy classifier based on low quality data
20091
15 200833
16 20078
17 200672
18
Study of the Probabilistic Information of a Random Set.
20038
19 200293
20
Examples of Independence for Imprecise Probabilities
199959

About Inés Couso

Inés Couso is a scholar working on Statistics and Probability, Management Science and Operations Research, Artificial Intelligence, Computational Theory and Mathematics and Medical Laboratory Technology, having authored 111 papers that have together received 2.1k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (53 papers), Fuzzy Systems and Optimization (44 papers), Fuzzy Logic and Control Systems (43 papers), Rough Sets and Fuzzy Logic (23 papers), Bayesian Modeling and Causal Inference (20 papers), Neural Networks and Applications (12 papers), Evolutionary Algorithms and Applications (9 papers) and Advanced Battery Technologies Research (8 papers). The work is most often cited by research in Statistics and Probability (791 citations), Management Science and Operations Research (910 citations), Artificial Intelligence (1.2k citations), General Decision Sciences (52 citations) and Computational Theory and Mathematics (436 citations). Inés Couso has collaborated with scholars based in Spain, France and Germany. Frequent co-authors include Luciano Sánchez, Didier Dubois, Serafı́n Moral, Pedro Gil, Peter Walley, Enrique Miranda, Ana M. Palacios, Susana Montes, Jorge Casillas and José Otero. Their work appears in journals such as International Journal of Approximate Reasoning, Fuzzy Sets and Systems, Information Sciences, IEEE Transactions on Fuzzy Systems 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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