Ángel Fernández-Leal

8 papers and 229 indexed citations i.

About

Ángel Fernández-Leal is a scholar working on Artificial Intelligence, Signal Processing and Computer Networks and Communications. According to data from OpenAlex, Ángel Fernández-Leal has authored 8 papers receiving a total of 229 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Artificial Intelligence, 3 papers in Signal Processing and 2 papers in Computer Networks and Communications. Recurrent topics in Ángel Fernández-Leal’s work include Machine Learning and Data Classification (2 papers), Machine Learning and Algorithms (2 papers) and Time Series Analysis and Forecasting (2 papers). Ángel Fernández-Leal is often cited by papers focused on Machine Learning and Data Classification (2 papers), Machine Learning and Algorithms (2 papers) and Time Series Analysis and Forecasting (2 papers). Ángel Fernández-Leal collaborates with scholars based in Spain and United States. Ángel Fernández-Leal's co-authors include Eduardo Mosqueira-Rey, Elena Hernández-Pereira, José Bobes-Bascarán, David Alonso-Ríos, Vicente Moret‐Bonillo and Diego Álvarez-Estévez and has published in prestigious journals such as Expert Systems with Applications, Knowledge-Based Systems and Neural Computing and Applications.

In The Last Decade

Co-authorship network of co-authors of Ángel Fernández-Leal i

Fields of papers citing papers by Ángel Fernández-Leal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ángel Fernández-Leal. 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 Ángel Fernández-Leal. The network helps show where Ángel Fernández-Leal may publish in the future.

Countries citing papers authored by Ángel Fernández-Leal

Since Specialization
Citations

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

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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