Fernando Rojas
Impact in
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- Stock Market Forecasting Methods
- Artificial Intelligence top 5%
- Neural Networks and Applications
- Fuzzy Logic and Control Systems
- Metaheuristic Optimization Algorithms Research
- Evolutionary Algorithms and Applications
Papers in
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- Neural Networks and Applications 18
- Fuzzy Logic and Control Systems 14
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- Blind Source Separation Techniques 8
- Time Series Analysis and Forecasting 5
- Co-authors
- Ignacio Rojas (37 shared papers)Olga Valenzuela (30 shared papers)H. Pomares (19 shared papers)Luis Javier Herrera (17 shared papers)Alberto Guillén (8 shared papers)M. Pasadas (2 shared papers)Jesús González (10 shared papers)Miguel Damas (2 shared papers)
In The Last Decade
Fernando Rojas
55 papers receiving 840 citations
Peers
Comparison fields: 5 of 133
- Management Science and Operations Research 145
- Artificial Intelligence 350
- Signal Processing 91
- Computer Vision and Pattern Recognition 113
- Control and Systems Engineering 107
Countries citing papers authored by Fernando Rojas
This map shows the geographic impact of Fernando Rojas'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 Fernando Rojas with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fernando Rojas more than expected).
Fields of papers citing papers by Fernando Rojas
This network shows the impact of papers produced by Fernando Rojas. 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 Fernando Rojas. The network helps show where Fernando Rojas may publish in the future.
Co-authors
The 25 scholars most cited alongside Fernando Rojas, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2007 | 175 | |
| 2 | 2007 | 137 | |
| 3 | 2012 | 59 | |
| 4 | 2013 | 45 | |
| 5 | 2017 | 41 | |
| 6 | 2006 | 38 | |
| 7 | 2006 | 34 | |
| 8 | 2019 | 33 | |
| 9 | 2004 | 25 | |
| 10 | 2007 | 19 | |
| 11 | 2002 | 19 | |
| 12 | 2019 | 17 | |
| 13 | 2015 | 15 | |
| 14 | 2007 | 15 | |
| 15 | 2021 | 15 | |
| 16 | 2010 | 14 | |
| 17 | 2020 | 13 | |
| 18 | 2001 | 10 | |
| 19 | 2019 | 10 | |
| 20 | 2002 | 10 |
About Fernando Rojas
Fernando Rojas is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Biomedical Engineering and Molecular Biology, having authored 66 papers that have together received 876 indexed citations. Recurring topics across this work include Neural Networks and Applications (18 papers), Fuzzy Logic and Control Systems (14 papers), Blind Source Separation Techniques (8 papers), Spectroscopy and Chemometric Analyses (7 papers), Time Series Analysis and Forecasting (5 papers), Advanced Image Fusion Techniques (4 papers), Stock Market Forecasting Methods (4 papers) and Remote-Sensing Image Classification (4 papers). The work is most often cited by research in Management Science and Operations Research (145 citations), Artificial Intelligence (350 citations), Signal Processing (91 citations), Computer Vision and Pattern Recognition (113 citations) and Control and Systems Engineering (107 citations). Fernando Rojas has collaborated with scholars based in Spain, Colombia and Cuba. Frequent co-authors include Ignacio Rojas, Olga Valenzuela, H. Pomares, Luis Javier Herrera, Alberto Guillén, M. Pasadas, Jesús González, Miguel Damas, Francisco Ortuño and Daniel Castillo-Secilla. Their work appears in journals such as Neurocomputing, Neural Processing Letters, International Journal of Approximate Reasoning, BMC Bioinformatics and Fuzzy Sets and Systems.
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.