Daniel Paternain
Impact in
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- Multi-Criteria Decision Making
- Statistics and Probability top 2%
- Fuzzy Systems and Optimization
Papers in
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- Multi-Criteria Decision Making 30
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- Fuzzy Logic and Control Systems 12
- Neural Networks and Applications 5
- Co-authors
- Humberto Bustince (45 shared papers)Radko Mesiar (19 shared papers)Gleb Beliakov (10 shared papers)Mikel Galar (17 shared papers)Edurne Barrenechea (9 shared papers)Benjamín Bedregal (6 shared papers)Aránzazu Jurío (14 shared papers)Javier Fernández (9 shared papers)
In The Last Decade
Daniel Paternain
55 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 101
- Management Science and Operations Research 523
- Statistics and Probability 237
- Signal Processing 196
- Computational Theory and Mathematics 273
- Artificial Intelligence 344
Countries citing papers authored by Daniel Paternain
This map shows the geographic impact of Daniel Paternain'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 Daniel Paternain with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Paternain more than expected).
Fields of papers citing papers by Daniel Paternain
This network shows the impact of papers produced by Daniel Paternain. 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 Daniel Paternain. The network helps show where Daniel Paternain may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Paternain, 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 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 111 | |
| 2 | 2011 | 71 | |
| 3 | 2014 | 62 | |
| 4 | 2015 | 55 | |
| 5 | 2015 | 52 | |
| 6 | 2016 | 51 | |
| 7 | 2010 | 48 | |
| 8 | 2013 | 46 | |
| 9 | 2020 | 43 | |
| 10 | 2012 | 43 | |
| 11 | 2010 | 37 | |
| 12 | 2015 | 37 | |
| 13 | 2011 | 35 | |
| 14 | 2014 | 35 | |
| 15 | 2018 | 21 | |
| 16 | 2018 | 20 | |
| 17 | 2015 | 18 | |
| 18 | 2017 | 16 | |
| 19 | 2011 | 16 | |
| 20 | 2013 | 15 |
About Daniel Paternain
Daniel Paternain is a scholar working on Management Science and Operations Research, Artificial Intelligence, Computational Theory and Mathematics, Computer Vision and Pattern Recognition and Statistics and Probability, having authored 58 papers that have together received 1.0k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (30 papers), Rough Sets and Fuzzy Logic (21 papers), Fuzzy Systems and Optimization (16 papers), Fuzzy Logic and Control Systems (12 papers), Image Retrieval and Classification Techniques (7 papers), Advanced Algebra and Logic (5 papers), Neural Networks and Applications (5 papers) and Optimization and Mathematical Programming (5 papers). The work is most often cited by research in Management Science and Operations Research (523 citations), Statistics and Probability (237 citations), Signal Processing (196 citations), Computational Theory and Mathematics (273 citations) and Artificial Intelligence (344 citations). Daniel Paternain has collaborated with scholars based in Spain, Slovakia and Czechia. Frequent co-authors include Humberto Bustince, Radko Mesiar, Gleb Beliakov, Mikel Galar, Edurne Barrenechea, Benjamín Bedregal, Aránzazu Jurío, Javier Fernández, José Sanz and José M. Benítez. Their work appears in journals such as Information Sciences, Fuzzy Sets and Systems, International Journal of Intelligent Systems, International Journal of General Systems 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.