Luis Martı́nez

28.8k citations
465 papers · 21.6k indexed · 13 hit papers · h-index 67

Luis Martı́nez

439 papers receiving 20.9k citations

Hit Papers

Multiple-criter...160200020262008201750010001.5k2.0k

Peers

Luis Martı́nez
Comparison fields: 5 of 183
  • Management Science and Operations Research 15.8k
  • Computational Theory and Mathematics 6.3k
  • Artificial Intelligence 7.7k
  • Statistics and Probability 1.8k
  • Management of Technology and Innovation 1.1k
Replace Francisco Chiclana with:
Francisco Chiclana United Kingdom
Huchang Liao China
Jian‐qiang Wang China
Shyi‐Ming Chen Taiwan
Пэйдэ Лю China
Krassimir Atanassov Bulgaria
Guiwu Wei China
Harish Garg India
Yucheng Dong China
Gwo‐Hshiung Tzeng Taiwan
Luis Martı́nez relative to Francisco Chiclana United Kingdom Francisco Chiclana's profile →
Citations per field
00.5×1.5×2.0×
Francisco Chiclana · 1×
Citations per year

Countries citing papers authored by Luis Martı́nez

Since Specialization
Citations

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

Fields of papers citing papers by Luis Martı́nez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20245
2 20249
3 20242
4 20240
5 20246
6 20241
7 20241
8 20247
9 20241
10 20248
11 202327
12 20238
13 20237
14 202340
15 20233
16 202320
17 202313
18 202320
19 201613
20 20073

About Luis Martı́nez

Luis Martı́nez is a scholar working on Management Science and Operations Research, Computational Theory and Mathematics, Artificial Intelligence, Statistics and Probability and Statistics, Probability and Uncertainty, having authored 465 papers that have together received 21.6k indexed citations. Recurring topics across this work include Multi-Criteria Decision Making (284 papers), Rough Sets and Fuzzy Logic (99 papers), Cognitive Science and Mapping (61 papers), Bayesian Modeling and Causal Inference (48 papers), Fuzzy Logic and Control Systems (42 papers), Recommender Systems and Techniques (38 papers), Fuzzy Systems and Optimization (32 papers) and Optimization and Mathematical Programming (30 papers). The work is most often cited by research in Management Science and Operations Research (15.8k citations), Computational Theory and Mathematics (6.3k citations), Artificial Intelligence (7.7k citations), Statistics and Probability (1.8k citations) and Management of Technology and Innovation (1.1k citations). Luis Martı́nez has collaborated with scholars based in Spain, China and United Kingdom. Frequent co-authors include Francisco Herrera, Rosa M. Rodríguez, Enrique Herrera‐Viedma, Iván Palomares, Álvaro Labella, Francisco Mata, Jun Liu, Raciel Yera, Yucheng Dong and Zhen‐Song Chen. Their work appears in journals such as Information Sciences, IEEE Transactions on Fuzzy Systems, Expert Systems with Applications, Computers & Industrial Engineering 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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