César Hervás‐Martínez

8.0k total citations · 1 hit paper
220 papers, 5.5k citations indexed

About

César Hervás‐Martínez is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Analytical Chemistry. According to data from OpenAlex, César Hervás‐Martínez has authored 220 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 105 papers in Artificial Intelligence, 26 papers in Computer Vision and Pattern Recognition and 23 papers in Analytical Chemistry. Recurrent topics in César Hervás‐Martínez's work include Neural Networks and Applications (47 papers), Metaheuristic Optimization Algorithms Research (32 papers) and Evolutionary Algorithms and Applications (27 papers). César Hervás‐Martínez is often cited by papers focused on Neural Networks and Applications (47 papers), Metaheuristic Optimization Algorithms Research (32 papers) and Evolutionary Algorithms and Applications (27 papers). César Hervás‐Martínez collaborates with scholars based in Spain, United Kingdom and United States. César Hervás‐Martínez's 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 and has published in prestigious journals such as PLoS ONE, Analytical Chemistry and Journal of Cleaner Production.

In The Last Decade

César Hervás‐Martínez

210 papers receiving 5.2k citations

Hit Papers

Ordinal Regression Methods: Survey and Experimental Study 2015 2026 2018 2022 2015 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Ordinal Regression Methods: Survey and Experimental Study
    2015 281 citations Pedro Antonio Gutiérrez, María Pérez‐Ortiz et al. IEEE Transactions on Knowledge and Data Engineering profile →

Peers

César Hervás‐Martínez
Pedro Antonio Gutiérrez Spain
Haifeng Li China
Chi‐Hyuck Jun South Korea
Stefano Ermon United States
Alaa Tharwat Egypt
Abdelhameed Ibrahim‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬ Egypt
Xiaohui Yuan United States
André C. P. L. F. de Carvalho Brazil
George C. Runger United States
Zenghui Wang South Africa
Pedro Antonio Gutiérrez Spain
César Hervás‐Martínez
Citations per year, relative to César Hervás‐Martínez César Hervás‐Martínez (= 1×) peers Pedro Antonio Gutiérrez

Countries citing papers authored by César Hervás‐Martínez

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

20 of 20 papers shown
1.
Martínez-Estudillo, Francisco José, et al.. (2025). Splitting criteria for ordinal decision trees: An experimental study. Pattern Recognition. 171. 112273–112273.
2.
Guijo-Rubio, David, et al.. (2025). dlordinal: A Python package for deep ordinal classification. Neurocomputing. 622. 129305–129305. 3 indexed citations
3.
Guijo-Rubio, David, et al.. (2025). Enhancing wind speed prediction in wind farms through ordinal classification. Energy and AI. 22. 100596–100596.
4.
Guijo-Rubio, David, et al.. (2024). Convolutional- and Deep Learning-Based Techniques for Time Series Ordinal Classification. IEEE Transactions on Cybernetics. 55(2). 537–549. 2 indexed citations
5.
Pérez‐Aracil, Jorge, et al.. (2024). Fuzzy-based ensemble methodology for accurate long-term prediction and interpretation of extreme significant wave height events. Applied Ocean Research. 153. 104273–104273. 3 indexed citations
6.
Gutiérrez, Pedro Antonio, et al.. (2023). Exponential loss regularisation for encouraging ordinal constraint to shotgun stocks quality assessment. Applied Soft Computing. 138. 110191–110191. 11 indexed citations
7.
Guijo-Rubio, David, et al.. (2023). Cluster analysis and forecasting of viruses incidence growth curves: Application to SARS-CoV-2. Expert Systems with Applications. 225. 120103–120103. 3 indexed citations
8.
Rosati, Riccardo, et al.. (2022). A novel deep ordinal classification approach for aesthetic quality control classification. Neural Computing and Applications. 34(14). 11625–11639. 20 indexed citations
9.
Gutiérrez, Pedro Antonio, et al.. (2022). Deep learning based hierarchical classifier for weapon stock aesthetic quality control assessment. Computers in Industry. 144. 103786–103786. 16 indexed citations
10.
11.
Guijo-Rubio, David, et al.. (2020). Short- and long-term energy flux prediction using Multi-Task Evolutionary Artificial Neural Networks. Ocean Engineering. 216. 108089–108089. 15 indexed citations
12.
Martín, Alejandro, et al.. (2020). Optimising Convolutional Neural Networks using a Hybrid Statistically-driven Coral Reef Optimisation algorithm. Applied Soft Computing. 90. 106144–106144. 24 indexed citations
13.
Gutiérrez, Pedro Antonio, et al.. (2020). A novel approach for global solar irradiation forecasting on tilted plane using Hybrid Evolutionary Neural Networks. Journal of Cleaner Production. 287. 125577–125577. 18 indexed citations
14.
Comino, Francisco, David Guijo-Rubio, Manuel Ruiz de Adana, & César Hervás‐Martínez. (2019). Validation of multitask artificial neural networks to model desiccant wheels activated at low temperature. International Journal of Refrigeration. 100. 434–442. 10 indexed citations
15.
Durán-Rosal, Antonio M., Pedro Antonio Gutiérrez, A. Carmona-Poyato, & César Hervás‐Martínez. (2019). A hybrid dynamic exploitation barebones particle swarm optimisation algorithm for time series segmentation. Neurocomputing. 353. 45–55. 14 indexed citations
16.
Durán-Rosal, Antonio M., Pedro Antonio Gutiérrez, Francisco José Martínez-Estudillo, & César Hervás‐Martínez. (2018). Simultaneous optimisation of clustering quality and approximation error for time series segmentation. Information Sciences. 442-443. 186–201. 4 indexed citations
17.
Pérez‐Ortiz, María, et al.. (2017). Dynamically weighted evolutionary ordinal neural network for solving an imbalanced liver transplantation problem. Artificial Intelligence in Medicine. 77. 1–11. 38 indexed citations
18.
Durán-Rosal, Antonio M., Pedro Antonio Gutiérrez, Sancho Salcedo‐Sanz, & César Hervás‐Martínez. (2017). A statistically-driven Coral Reef Optimization algorithm for optimal size reduction of time series. Applied Soft Computing. 63. 139–153. 24 indexed citations
19.
Fernández, Juan Carlos Fernández, Sancho Salcedo‐Sanz, Pedro Antonio Gutiérrez, Enrique Alexandre, & César Hervás‐Martínez. (2015). Significant wave height and energy flux range forecast with machine learning classifiers. Engineering Applications of Artificial Intelligence. 43. 44–53. 58 indexed citations
20.
Gutiérrez, Pedro Antonio, María Pérez‐Ortiz, Javier Sánchez‐Monedero, Francisco Fernández‐Navarro, & César Hervás‐Martínez. (2015). Ordinal Regression Methods: Survey and Experimental Study. IEEE Transactions on Knowledge and Data Engineering. 28(1). 127–146. 281 indexed citations breakdown →

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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