Luis Miguel Antonio
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 2%
- Management Science and Operations Research top 10%
- Control and Systems Engineering
- Electrical and Electronic Engineering
- Topics
- Metaheuristic Optimization Algorithms Research (11 papers)Advanced Multi-Objective Optimization Algorithms (10 papers)Evolutionary Algorithms and Applications (9 papers)
In The Last Decade
Luis Miguel Antonio
14 papers receiving 431 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 331
- Computational Theory and Mathematics 297
- Management Science and Operations Research 47
- Control and Systems Engineering 44
- Electrical and Electronic Engineering 28
Countries citing papers authored by Luis Miguel Antonio
This map shows the geographic impact of Luis Miguel Antonio'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 Miguel Antonio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luis Miguel Antonio more than expected).
Fields of papers citing papers by Luis Miguel Antonio
This network shows the impact of papers produced by Luis Miguel Antonio. 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 Miguel Antonio. The network helps show where Luis Miguel Antonio may publish in the future.
Co-authorship network of co-authors of Luis Miguel Antonio
This figure shows the co-authorship network connecting the top 25 collaborators of Luis Miguel Antonio. A scholar is included among the top collaborators of Luis Miguel Antonio based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Luis Miguel Antonio. Luis Miguel Antonio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | Analyzing the Usefulness of ThingFO as a Foundational Ontology for Sciences | 3 |
| 3 | 11 | |
| 4 | 21 | |
| 5 | 4 | |
| 6 | 148 | |
| 7 | 21 | |
| 8 | 9 | |
| 9 | 3 | |
| 10 | Developments in kernel design | 2 |
| 11 | 197 | |
| 12 | A Theory for heterogeneous neuron models based on similarity | 1 |
| 13 | A Case study in neural network training with the breeder genetic algorithm | 2 |
| 14 | A Study in function optimization with the breeder genetic algorithm | 9 |
About Luis Miguel Antonio
Luis Miguel Antonio is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Information Systems and Management, having authored 14 papers that have together received 439 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (11 papers), Advanced Multi-Objective Optimization Algorithms (10 papers) and Evolutionary Algorithms and Applications (9 papers). The work is most often cited by research in Computational Theory and Mathematics (297 citations), Artificial Intelligence (331 citations) and Computational Mathematics (3 citations). Luis Miguel Antonio has collaborated with scholars based in Mexico, Chile and Spain. Frequent co-authors include Carlos A. Coello Coello, Elizabeth Montero, Saúl Zapotecas–Martínez and María-Cristina Riff. Their work appears in journals such as IEEE Access, IEEE Transactions on Evolutionary Computation and Soft Computing.
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.