César Hervás‐Martínez
- Artificial Intelligence top 0.5%
- Electrical and Electronic Engineering top 5%
- Plant Science top 5%
- Computer Vision and Pattern Recognition top 2%
- Environmental Engineering top 2%
- Co-authors
- Pedro Antonio GutiérrezFrancisco Fernández‐NavarroMaría Pérez‐OrtizNicolás García‐PedrajasJavier Sánchez‐MonederoSebastián VenturaFrancisca López GranadosJosé M. Peña
- Topics
- Neural Networks and Applications (47 papers)Metaheuristic Optimization Algorithms Research (32 papers)Evolutionary Algorithms and Applications (27 papers)
- Partner nations
- SpainUnited KingdomUnited States
In The Last Decade
César Hervás‐Martínez
210 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 192
- Artificial Intelligence 2.3k
- Electrical and Electronic Engineering 652
- Plant Science 538
- Computer Vision and Pattern Recognition 529
- Environmental Engineering 516
Countries citing papers authored by César Hervás‐Martínez
This map shows the geographic impact of César Hervás‐Martínez'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 César Hervás‐Martínez with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites César Hervás‐Martínez more than expected).
Fields of papers citing papers by César Hervás‐Martínez
This network shows the impact of papers produced by César Hervás‐Martínez. 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 César Hervás‐Martínez. The network helps show where César Hervás‐Martínez may publish in the future.
Co-authorship network of co-authors of César Hervás‐Martínez
This figure shows the co-authorship network connecting the top 25 collaborators of César Hervás‐Martínez. A scholar is included among the top collaborators of César Hervás‐Martínez 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 César Hervás‐Martínez. César Hervás‐Martínez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 11 | |
| 7 | 3 | |
| 8 | 20 | |
| 9 | 16 | |
| 10 | 14 | |
| 11 | 15 | |
| 12 | 24 | |
| 13 | 18 | |
| 14 | 10 | |
| 15 | 14 | |
| 16 | 4 | |
| 17 | 38 | |
| 18 | 24 | |
| 19 | 58 | |
| 20 | Ordinal Regression Methods: Survey and Experimental Studybreakdown → | 281 |
About César Hervás‐Martínez
César Hervás‐Martínez is a scholar working on Artificial Intelligence, Analytical Chemistry and Environmental Engineering, having authored 220 papers that have together received 5.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (47 papers), Metaheuristic Optimization Algorithms Research (32 papers) and Evolutionary Algorithms and Applications (27 papers). The work is most often cited by research in Artificial Intelligence (2.3k citations), Computer Science Applications (254 citations) and Environmental Engineering (516 citations). César Hervás‐Martínez has collaborated with scholars based in Spain, United Kingdom and United States. Frequent co-authors include Pedro Antonio Gutiérrez, Francisco Fernández‐Navarro, María Pérez‐Ortiz, Nicolás García‐Pedrajas, Javier Sánchez‐Monedero, Sebastián Ventura, Francisca López Granados, José M. Peña, Juan Carlos Fernández Fernández and Francisco José Martínez-Estudillo. Their work appears in journals such as PLoS ONE, Analytical Chemistry and Journal of Cleaner Production.
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.