Antonio J. Rivera

2.2k total citations
40 papers, 1.2k citations indexed

About

Antonio J. Rivera is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition. According to data from OpenAlex, Antonio J. Rivera has authored 40 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Artificial Intelligence, 7 papers in Management Science and Operations Research and 6 papers in Computer Vision and Pattern Recognition. Recurrent topics in Antonio J. Rivera's work include Text and Document Classification Technologies (10 papers), Neural Networks and Applications (9 papers) and Imbalanced Data Classification Techniques (7 papers). Antonio J. Rivera is often cited by papers focused on Text and Document Classification Technologies (10 papers), Neural Networks and Applications (9 papers) and Imbalanced Data Classification Techniques (7 papers). Antonio J. Rivera collaborates with scholars based in Spain, United Kingdom and Saudi Arabia. Antonio J. Rivera's co-authors include María José del Jesús, Francisco Herrera, Francisco Charte, María Dolores Pérez-Godoy, Francisco Martínez, María Pilar Frías, C. J. Carmona, B. García-Domingo, J. Aguilera and Alberto Fernández and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Information Sciences.

In The Last Decade

Antonio J. Rivera

38 papers receiving 1.2k citations

Peers

Antonio J. Rivera
Jiangtao Ren China
Francisco Charte Spain
Sara del Río Spain
Dae-Ki Kang South Korea
Juan Gómez‐Romero Spain
Iffat A. Gheyas United Kingdom
Aditi Sharan India
Yangming Zhou China
Jiangtao Ren China
Antonio J. Rivera
Citations per year, relative to Antonio J. Rivera Antonio J. Rivera (= 1×) peers Jiangtao Ren

Countries citing papers authored by Antonio J. Rivera

Since Specialization
Citations

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

Fields of papers citing papers by Antonio J. Rivera

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Antonio J. Rivera. 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 Antonio J. Rivera. The network helps show where Antonio J. Rivera may publish in the future.

Co-authorship network of co-authors of Antonio J. Rivera

This figure shows the co-authorship network connecting the top 25 collaborators of Antonio J. Rivera. A scholar is included among the top collaborators of Antonio J. Rivera 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 Antonio J. Rivera. Antonio J. Rivera 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.
Rivera, Antonio J., et al.. (2025). Transfer Learning with Foundational Models for Time Series Forecasting using Low-Rank Adaptations. Information Fusion. 123. 103247–103247. 5 indexed citations
2.
Rivera, Antonio J., et al.. (2025). Importance of prickly pear (Opuntia spp) cultivation for sustainable agricultural systems and climate change resilient. GSC Advanced Research and Reviews. 23(3). 117–123.
3.
Pérez-Godoy, María Dolores, et al.. (2024). DESReg: Dynamic Ensemble Selection library for Regression tasks. Neurocomputing. 580. 127487–127487.
4.
Ducange, Pietro, et al.. (2024). Nets4Learning: A Web Platform for Designing and Testing ANN/DNN Models. Electronics. 13(22). 4378–4378. 1 indexed citations
5.
Rivera, Antonio J., et al.. (2023). XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department. Artificial Intelligence in Medicine. 137. 102494–102494. 4 indexed citations
6.
Martínez, Francisco, María Pilar Frías, María Dolores Pérez-Godoy, & Antonio J. Rivera. (2022). Time Series Forecasting by Generalized Regression Neural Networks Trained With Multiple Series. IEEE Access. 10. 3275–3283. 9 indexed citations
7.
Charte, Francisco, Antonio J. Rivera, David Charte, María José del Jesús, & Francisco Herrera. (2018). Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository. Neurocomputing. 289. 68–85. 24 indexed citations
8.
Martínez, Francisco, María Pilar Frías, María Dolores Pérez-Godoy, & Antonio J. Rivera. (2017). A methodology for applying k-nearest neighbor to time series forecasting. Artificial Intelligence Review. 52(3). 2019–2037. 105 indexed citations
9.
Charte, Francisco, Antonio J. Rivera, María José del Jesús, & Francisco Herrera. (2017). Dealing with difficult minority labels in imbalanced mutilabel data sets. Neurocomputing. 326-327. 39–53. 46 indexed citations
10.
Charte, Francisco, Inmaculada Romero, María Dolores Pérez-Godoy, Antonio J. Rivera, & Eulógio Castro. (2017). Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass. Computers & Chemical Engineering. 101. 23–30. 22 indexed citations
11.
Charte, Francisco, Antonio J. Rivera, María José del Jesús, & Francisco Herrera. (2015). Addressing imbalance in multilabel classification: Measures and random resampling algorithms. Neurocomputing. 163. 3–16. 193 indexed citations
12.
Charte, Francisco, Antonio J. Rivera, María José del Jesús, & Francisco Herrera. (2015). QUINTA: A question tagging assistant to improve the answering ratio in electronic forums. 1–6. 13 indexed citations
13.
Charte, Francisco, Antonio J. Rivera, María José del Jesús, & Francisco Herrera. (2014). LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification. IEEE Transactions on Neural Networks and Learning Systems. 25(10). 1842–1854. 21 indexed citations
14.
Pérez-Godoy, María Dolores, Antonio J. Rivera, C. J. Carmona, & María José del Jesús. (2014). Training algorithms for Radial Basis Function Networks to tackle learning processes with imbalanced data-sets. Applied Soft Computing. 25. 26–39. 25 indexed citations
15.
Rivera, Antonio J., et al.. (2011). A study on the medium-term forecasting using exogenous variable selection of the extra-virgin olive oil with soft computing methods. Applied Intelligence. 34(3). 331–346. 1 indexed citations
16.
Pérez-Godoy, María Dolores, Antonio J. Rivera, María José del Jesús, et al.. (2010). CO2RBFN for short-term forecasting of the extra virgin olive oil price in the Spanish market. International Journal of Hybrid Intelligent Systems. 7(1). 75–87. 4 indexed citations
17.
Rivera, Antonio J., Ignacio Rojas, Julio Ortega, & María José del Jesús. (2006). A new hybrid methodology for cooperative-coevolutionary optimization of radial basis function networks. Soft Computing. 11(7). 655–668. 18 indexed citations
18.
Rivera, Antonio J., et al.. (1997). Anticuerpos anti-Echinococcus (hidatidosis). Mediante hemaglutinación pasiva, en sujetos expuestos a riesgo. 44(4). 233–239. 3 indexed citations
19.
Pazos, Alejandro, et al.. (1996). RECOGNITION OF HUMAN MOVEMENT PATTERNS. ISBS - Conference Proceedings Archive. 1(1). 1 indexed citations
20.
Casado, J.A., Manuel Mosquera, Antonio J. Rivera, Flor Rodríguez‐Prieto, & J. Arturo Santaballa. (1983). A calculator program for the optimization of physico-chemical parameters by unidimensional search. Computers & Chemistry. 7(4). 209–213. 24 indexed citations

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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