Antonio M. Gómez-Orellana

Orcid: 0000-0002-1929-2408

According to our database1, Antonio M. Gómez-Orellana authored at least 11 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
EBANO: A novel Ensemble BAsed on uNimodal Ordinal classifiers for the prediction of significant wave height.
Knowl. Based Syst., 2024

ORFEO: Ordinal classifier and Regressor Fusion for Estimating an Ordinal categorical target.
Eng. Appl. Artif. Intell., 2024

Data Augmentation Techniques for Extreme Wind Prediction Improvement.
Proceedings of the Bioinspired Systems for Translational Applications: From Robotics to Social Engineering, 2024

Energy Flux Prediction Using an Ordinal Soft Labelling Strategy.
Proceedings of the Bioinspired Systems for Translational Applications: From Robotics to Social Engineering, 2024

Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm.
Proceedings of the Bioinspired Systems for Translational Applications: From Robotics to Social Engineering, 2024

Age Estimation Using Soft Labelling Ordinal Classification Approaches.
Proceedings of the Advances in Artificial Intelligence, 2024

2023
An Evolutionary Artificial Neural Network approach for spatio-temporal wave height time series reconstruction.
Appl. Soft Comput., October, 2023

2022
COVID-19 contagion forecasting framework based on curve decomposition and evolutionary artificial neural networks: A case study in Andalusia, Spain.
Expert Syst. Appl., 2022

Gamifying the Classroom for the Acquisition of Skills Associated with Machine Learning: A Two-Year Case Study.
Proceedings of the International Joint Conference 15th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2022) 13th International Conference on EUropean Transnational Education (ICEUTE 2022), 2022

2020
Prediction of convective clouds formation using evolutionary neural computation techniques.
Neural Comput. Appl., 2020

2018
Distribution-Based Discretisation and Ordinal Classification Applied to Wave Height Prediction.
Proceedings of the Intelligent Data Engineering and Automated Learning - IDEAL 2018, 2018


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