Andrés Cano

32 papers receiving 379 citations

Peers

Andrés Cano
Comparison fields: 5 of 69
  • Artificial Intelligence 332
  • Management Science and Operations Research 120
  • Signal Processing 80
  • Computational Theory and Mathematics 91
  • Statistics and Probability 32
Replace Alessandro Antonucci with:
Alessandro Antonucci Switzerland
Andrés R. Masegosa Spain
Huizi Cui China
Y. Yurramendi Spain
Silvia Acid Spain
BW Pilsworth United Kingdom
Jiří Vomlel Czechia
Adam Niewiadomski Poland
David Harmanec United States
Jiwen Guan China
Andrés Cano relative to Alessandro Antonucci Switzerland Alessandro Antonucci's profile →
Citations per field
00.5×1.5×1.9×
Alessandro Antonucci · 1×
Citations per year

Countries citing papers authored by Andrés Cano

Since Specialization
Citations

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

Fields of papers citing papers by Andrés Cano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Andrés Cano, 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 Andrés Cano Line = papers co-authored together Andrés Cano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201164
2 200049
3 200239
4 200035
5 200230
6 201122
7 200620
8 200218
9
A Review of Propagation Algorithms for Imprecise Probabilities.
199915
10 202112
11 201812
12 201012
13 200512
14 201211
15 200611
16 20028
17 20167
18 20127
19 20195
20 20035

About Andrés Cano

Andrés Cano is a scholar working on Artificial Intelligence, Signal Processing, Information Systems, Computational Theory and Mathematics and Management Science and Operations Research, having authored 33 papers that have together received 421 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (30 papers), Data Management and Algorithms (13 papers), Data Mining Algorithms and Applications (10 papers), AI-based Problem Solving and Planning (7 papers), Rough Sets and Fuzzy Logic (5 papers), Data Quality and Management (3 papers), Statistical Methods and Bayesian Inference (3 papers) and Gene expression and cancer classification (2 papers). The work is most often cited by research in Artificial Intelligence (332 citations), Management Science and Operations Research (120 citations), Signal Processing (80 citations), Computational Theory and Mathematics (91 citations) and Statistics and Probability (32 citations). Andrés Cano has collaborated with scholars based in Spain, Denmark and Switzerland. Frequent co-authors include Serafı́n Moral, Antonio Salmerón, Luis M. de Campos, Javier G. Castellano, Joaquín Abellán, Fábio Gagliardi Cozman, Thomas Lukasiewicz, Juan M. Fernández‐Luna, Andrés R. Masegosa and Alessandro Antonucci. Their work appears in journals such as International Journal of Approximate Reasoning, International Journal of Intelligent Systems, International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, Networks and Statistical Applications in Genetics and Molecular Biology.

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.

Explore authors with similar magnitude of impact