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ORCIDJorge Pérez-Aracil
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2020 – today
- 2024
[j14]Vinícius G. Costa
, Jorge Pérez-Aracil, Sancho Salcedo-Sanz, Carlos Eduardo Pedreira:
Evolving interpretable decision trees for reinforcement learning. Artif. Intell. 327: 104057 (2024)- [j13]César Peláez-Rodríguez, Ricardo Torres-Lopez, Jorge Pérez-Aracil, Nieves López-Laguna, S. Sánchez-Rodríguez, Sancho Salcedo-Sanz:
An explainable machine learning approach for hospital emergency department visits forecasting using continuous training and multi-model regression. Comput. Methods Programs Biomed. 245: 108033 (2024) - [j12]César Peláez-Rodríguez, Jorge Pérez-Aracil, Dusan Fister, Ricardo Torres-Lopez, Sancho Salcedo-Sanz:
Bike sharing and cable car demand forecasting using machine learning and deep learning multivariate time series approaches. Expert Syst. Appl. 238(Part E): 122264 (2024) - [j11]Helena Liz-López, Javier Huertas-Tato, Jorge Pérez-Aracil, Carlos Casanova-Mateo, Julia Sanz-Justo, David Camacho:
Spain on fire: A novel wildfire risk assessment model based on image satellite processing and atmospheric information. Knowl. Based Syst. 283: 111198 (2024) - [j10]César Peláez-Rodríguez, Jorge Pérez-Aracil, Cosmin Madalin Marina, Luis Prieto-Godino, Carlos Casanova-Mateo, Pedro Antonio Gutiérrez, Sancho Salcedo-Sanz:
A general explicable forecasting framework for weather events based on ordinal classification and inductive rules combined with fuzzy logic. Knowl. Based Syst. 291: 111556 (2024) - [c9]Cosmin Madalin Marina, Eugenio Lorente-Ramos, Rafael Ayllón-Gavilán, Pedro Antonio Gutiérrez, Jorge Pérez-Aracil, Sancho Salcedo-Sanz:
Multivariate-Autoencoder Flow-Analogue Method for Heat Waves Reconstruction. CAEPIA 2024: 223-232 - [c8]Gabriel M. C. Leite, Jorge Pérez-Aracil, Carolina Gil Marcelino, Gabriel García-Gutiérrez, Milan Prodanovic, Enrique García-Quismondo, Sergio Pinilla, Jesús Palma, Silvia Jiménez-Fernández, Sancho Salcedo-Sanz:
Machine Learning Health Estimation for Lithium-Ion Batteries Under Varied Conditions. IWINAC (2) 2024: 275-282 - [c7]Antonio M. Gómez-Orellana, Víctor Manuel Vargas, Pedro Antonio Gutiérrez, Jorge Pérez-Aracil, Sancho Salcedo-Sanz, César Hervás-Martínez, David Guijo-Rubio:
Energy Flux Prediction Using an Ordinal Soft Labelling Strategy. IWINAC (2) 2024: 283-292 - [c6]Antonio M. Gómez-Orellana, Víctor Manuel Vargas, David Guijo-Rubio, Jorge Pérez-Aracil, Pedro Antonio Gutiérrez, Sancho Salcedo-Sanz, César Hervás-Martínez:
Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm. IWINAC (2) 2024: 293-302 - [c5]Marta Vega-Bayo, Antonio Manuel Gómez-Orellana, Víctor Manuel Vargas Yun, David Guijo-Rubio, Laura Cornejo-Bueno, Jorge Pérez-Aracil, Sancho Salcedo-Sanz:
Data Augmentation Techniques for Extreme Wind Prediction Improvement. IWINAC (2) 2024: 303-313 - [c4]Dusan Fister, César Peláez-Rodríguez, Laura Cornejo-Bueno, Jorge Pérez-Aracil, Sancho Salcedo-Sanz:
Autoencoder Framework for General Forecasting. IWINAC (2) 2024: 314-322 - [c3]César Peláez-Rodríguez, Laura Cornejo-Bueno, Dusan Fister, Jorge Pérez-Aracil, Sancho Salcedo-Sanz:
Prediction of Extreme Wave Heights via a Fuzzy-Based Cascade Ensemble Model. IWINAC (2) 2024: 323-332 - [c2]Waldemar Hugo LLamosas-Mayca, Eugenio Lorente-Ramos, Jorge Pérez-Aracil, Alejandro M. Hernández-Díaz, Manuel D. García-Román, Sancho Salcedo-Sanz:
Machine Learning as Applied to Shape Parameterization of Submerged Arch Structures. IWINAC (2) 2024: 333-344 - [i5]Gustau Camps-Valls, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Adrian Höhl, Andrea Castelletti, Aytac Pacal, Claire Robin, Francesco Martinuzzi, Ioannis Papoutsis, Ioannis Prapas, Jorge Pérez-Aracil, Katja Weigel, Maria Gonzalez-Calabuig, Markus Reichstein, Martin Rabel, Matteo Giuliani, Miguel D. Mahecha, Oana-Iuliana Popescu, Oscar J. Pellicer-Valero, Said Ouala, Sancho Salcedo-Sanz, Sebastian Sippel, Spyros Kondylatos, Tamara Happé, Tristan Williams:
AI for Extreme Event Modeling and Understanding: Methodologies and Challenges. CoRR abs/2406.20080 (2024) - 2023
- [j9]Dusan Fister, Jorge Pérez-Aracil, César Peláez-Rodríguez, Javier Del Ser, Sancho Salcedo-Sanz:
Accurate long-term air temperature prediction with Machine Learning models and data reduction techniques. Appl. Soft Comput. 136: 110118 (2023) - [j8]Jorge Pérez-Aracil, Alejandro Mateo Hernández-Díaz, Cosmin Madalin Marina, Sancho Salcedo-Sanz:
Improving numerical methods for the steel yield strain calculation in reinforced concrete members with Machine Learning algorithms. Expert Syst. Appl. 225: 119987 (2023) - [j7]César Peláez-Rodríguez, Jorge Pérez-Aracil, A. de Lopez-Diz, Carlos Casanova-Mateo, Dusan Fister, Silvia Jiménez-Fernández, Sancho Salcedo-Sanz:
Deep learning ensembles for accurate fog-related low-visibility events forecasting. Neurocomputing 549: 126435 (2023) - [j6]Carolina Gil Marcelino, Jorge Pérez-Aracil, Elizabeth F. Wanner, Silvia Jiménez-Fernández, Gabriel Matos Cardoso Leite, Sancho Salcedo-Sanz:
Cross-entropy boosted CRO-SL for optimal power flow in smart grids. Soft Comput. 27(10): 6549-6572 (2023) - [i4]Helena Liz-López, Javier Huertas-Tato, Jorge Pérez-Aracil, Carlos Casanova-Mateo, Julia Sanz-Justo, David Camacho:
Spain on Fire: A novel wildfire risk assessment model based on image satellite processing and atmospheric information. CoRR abs/2306.05045 (2023) - 2022
- [j5]Alejandro M. Hernández-Díaz, Jorge Pérez-Aracil, David Casillas-Perez, Emiliano Pereira, Sancho Salcedo-Sanz:
Hybridizing machine learning with metaheuristics for preventing convergence failures in mechanical models based on compression field theories. Appl. Soft Comput. 130: 109654 (2022) - [j4]Jorge Pérez-Aracil, Carlos Camacho-Gómez, Paul Reynolds, Emiliano Pereira, Sancho Salcedo-Sanz:
Optimal vibration isolation and alignment over non-rigid bases with the CRO-SL ensemble. Eng. Appl. Artif. Intell. 113: 104984 (2022) - [c1]Carolina Gil Marcelino, Elizabeth F. Wanner, Flávio V. C. Martins, Jorge Pérez-Aracil, Silvia Jiménez-Fernández, Sancho Salcedo-Sanz:
Solving the Optimal Active-Reactive Power Dispatch Problem in Smart Grids with the C-DEEPSO Algorithm. CEC 2022: 1-8 - [i3]Sancho Salcedo-Sanz, Jorge Pérez-Aracil, Guido Ascenso, Javier Del Ser, David Casillas-Pérez, Christopher Kadow, Dusan Fister, David Barriopedro, Ricardo García-Herrera, Marcello Restelli, Matteo Giuliani, Andrea Castelletti:
Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review. CoRR abs/2207.07580 (2022) - [i2]Dusan Fister, Jorge Pérez-Aracil, César Peláez-Rodríguez, Javier Del Ser, Sancho Salcedo-Sanz:
Accurate Long-term Air Temperature Prediction with a Fusion of Artificial Intelligence and Data Reduction Techniques. CoRR abs/2209.15424 (2022) - [i1]Jorge Pérez-Aracil, Carlos Camacho-Gómez, Eugenio Lorente-Ramos, Cosmin Madalin Marina, Sancho Salcedo-Sanz:
New Probabilistic-Dynamic Multi-Method Ensembles for Optimization based on the CRO-SL. CoRR abs/2212.00742 (2022) - 2021
- [j3]Jorge Pérez-Aracil, Carlos Camacho-Gómez, Alejandro Mateo Hernández-Díaz, Emiliano Pereira, David Camacho, Sancho Salcedo-Sanz:
Memetic coral reefs optimization algorithms for optimal geometrical design of submerged arches. Swarm Evol. Comput. 67: 100958 (2021) - 2020
- [j2]Jorge Pérez-Aracil, Carlos Camacho-Gómez, Alejandro M. Hernández-Díaz, Emiliano Pereira, Sancho Salcedo-Sanz:
Submerged Arches Optimal Design With a Multi-Method Ensemble Meta-Heuristic Approach. IEEE Access 8: 215057-215072 (2020)
2010 – 2019
- 2018
- [j1]Alejandro M. Hernández-Díaz, Andrés Bueno-Crespo, Jorge Pérez-Aracil, José M. Cecilia:
Multi-objective optimal design of submerged arches using extreme learning machine and evolutionary algorithms. Appl. Soft Comput. 71: 826-834 (2018)
Coauthor Index
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