Multi-objective optimal design of submerged arches using extreme learning machine and evolutionary algorithms. - Alejandro M. Hernández-Díaz; Andrés Bueno-Crespo; Jorge Pérez-Aracil; José M. Cecilia (Appl. Soft Comput., 2018)

Submerged Arches Optimal Design With a Multi-Method Ensemble Meta-Heuristic Approach. - Jorge Pérez-Aracil; Carlos Camacho-Gómez; Alejandro M. Hernández-Díaz; Emiliano Pereira; Sancho Salcedo-Sanz (IEEE Access, 2020)

Memetic coral reefs optimization algorithms for optimal geometrical design of submerged arches. - Jorge Pérez-Aracil; Carlos Camacho-Gómez; Alejandro Mateo Hernández-Díaz; Emiliano Pereira; David Camacho; Sancho Salcedo-Sanz (Swarm Evol. Comput., 2021)

Solving the Optimal Active-Reactive Power Dispatch Problem in Smart Grids with the C-DEEPSO Algorithm. - Carolina Gil Marcelino; Elizabeth F. Wanner; Flávio V. C. Martins; Jorge Pérez-Aracil; Silvia Jiménez-Fernández; Sancho Salcedo-Sanz (CEC, 2022)

Hybridizing machine learning with metaheuristics for preventing convergence failures in mechanical models based on compression field theories. - Alejandro M. Hernández-Díaz; Jorge Pérez-Aracil; David Casillas-Perez; Emiliano Pereira; Sancho Salcedo-Sanz (Appl. Soft Comput., 2022)

Analysis, Characterization, Prediction and Attribution of Extreme Atmospheric Events with Machine Learning: a Review. - 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 (CoRR, 2022)

Accurate Long-term Air Temperature Prediction with a Fusion of Artificial Intelligence and Data Reduction Techniques. - Dusan Fister; Jorge Pérez-Aracil; César Peláez-Rodríguez; Javier Del Ser; Sancho Salcedo-Sanz (CoRR, 2022)

New Probabilistic-Dynamic Multi-Method Ensembles for Optimization based on the CRO-SL. - Jorge Pérez-Aracil; Carlos Camacho-Gómez; Eugenio Lorente-Ramos; Cosmin Madalin Marina; Sancho Salcedo-Sanz (CoRR, 2022)

Optimal vibration isolation and alignment over non-rigid bases with the CRO-SL ensemble. - Jorge Pérez-Aracil; Carlos Camacho-Gómez; Paul Reynolds; Emiliano Pereira; Sancho Salcedo-Sanz (Eng. Appl. Artif. Intell., 2022)

Accurate long-term air temperature prediction with Machine Learning models and data reduction techniques. - Dusan Fister; Jorge Pérez-Aracil; César Peláez-Rodríguez; Javier Del Ser; Sancho Salcedo-Sanz (Appl. Soft Comput., 2023)

Cross-entropy boosted CRO-SL for optimal power flow in smart grids. - Carolina Gil Marcelino; Jorge Pérez-Aracil; Elizabeth F. Wanner; Silvia Jiménez-Fernández; Gabriel Matos Cardoso Leite; Sancho Salcedo-Sanz (Soft Comput., 2023)

Improving numerical methods for the steel yield strain calculation in reinforced concrete members with Machine Learning algorithms. - Jorge Pérez-Aracil; Alejandro Mateo Hernández-Díaz; Cosmin Madalin Marina; Sancho Salcedo-Sanz (Expert Syst. Appl., 2023)

Deep learning ensembles for accurate fog-related low-visibility events forecasting. - César Peláez-Rodríguez; Jorge Pérez-Aracil; A. de Lopez-Diz; Carlos Casanova-Mateo; Dusan Fister; Silvia Jiménez-Fernández; Sancho Salcedo-Sanz (Neurocomputing, 2023)

Multivariate-Autoencoder Flow-Analogue Method for Heat Waves Reconstruction. - Cosmin Madalin Marina; Eugenio Lorente-Ramos; Rafael Ayllón-Gavilán; Pedro Antonio Gutiérrez; Jorge Pérez-Aracil; Sancho Salcedo-Sanz (CAEPIA, 2024)

Autoencoder Framework for General Forecasting. - Dusan Fister; César Peláez-Rodríguez; Laura Cornejo-Bueno; Jorge Pérez-Aracil; Sancho Salcedo-Sanz (IWINAC (2), 2024)

Medium- and Long-Term Wind Speed Prediction Using the Multi-task Learning Paradigm. - Antonio M. Gómez-Orellana; Víctor Manuel Vargas; David Guijo-Rubio; Jorge Pérez-Aracil; Pedro Antonio Gutiérrez; Sancho Salcedo-Sanz; César Hervás-Martínez (IWINAC (2), 2024)

Energy Flux Prediction Using an Ordinal Soft Labelling Strategy. - Antonio M. Gómez-Orellana; Víctor Manuel Vargas; Pedro Antonio Gutiérrez; Jorge Pérez-Aracil; Sancho Salcedo-Sanz; César Hervás-Martínez; David Guijo-Rubio (IWINAC (2), 2024)

Machine Learning as Applied to Shape Parameterization of Submerged Arch Structures. - Waldemar Hugo LLamosas-Mayca; Eugenio Lorente-Ramos; Jorge Pérez-Aracil; Alejandro M. Hernández-Díaz; Manuel D. García-Román; Sancho Salcedo-Sanz (IWINAC (2), 2024)

Machine Learning Health Estimation for Lithium-Ion Batteries Under Varied Conditions. - 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 (IWINAC (2), 2024)

Prediction of Extreme Wave Heights via a Fuzzy-Based Cascade Ensemble Model. - César Peláez-Rodríguez; Laura Cornejo-Bueno; Dusan Fister; Jorge Pérez-Aracil; Sancho Salcedo-Sanz (IWINAC (2), 2024)

Data Augmentation Techniques for Extreme Wind Prediction Improvement. - Marta Vega-Bayo; Antonio Manuel Gómez-Orellana; Víctor Manuel Vargas Yun; David Guijo-Rubio; Laura Cornejo-Bueno; Jorge Pérez-Aracil; Sancho Salcedo-Sanz (IWINAC (2), 2024)

An explainable machine learning approach for hospital emergency department visits forecasting using continuous training and multi-model regression. - César Peláez-Rodríguez; Ricardo Torres-Lopez; Jorge Pérez-Aracil; Nieves López-Laguna; S. Sánchez-Rodríguez; Sancho Salcedo-Sanz (Comput. Methods Programs Biomed., 2024)

AI for Extreme Event Modeling and Understanding: Methodologies and Challenges. - 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; et al. (CoRR, 2024)

Identifying Key Drivers of Heatwaves: A Novel Spatio-Temporal Framework for Extreme Event Detection. - Jorge Pérez-Aracil; César Peláez-Rodríguez; Ronan McAdam; Antonello Squintu; Cosmin M. Marina; Eugenio Lorente-Ramos; Niklas Luther; Veronica Torralba; Enrico Scoccimarro; Leone Cavicchia; Matteo Giuliani; Eduardo Zorita; et al. (CoRR, 2024)

A general explicable forecasting framework for weather events based on ordinal classification and inductive rules combined with fuzzy logic. - César Peláez-Rodríguez; Jorge Pérez-Aracil; Cosmin Madalin Marina; Luis Prieto-Godino; Carlos Casanova-Mateo; Pedro Antonio Gutiérrez; Sancho Salcedo-Sanz (Knowl. Based Syst., 2024)

Spain on fire: A novel wildfire risk assessment model based on image satellite processing and atmospheric information. - Helena Liz-López; Javier Huertas-Tato; Jorge Pérez-Aracil; Carlos Casanova-Mateo; Julia Sanz-Justo; David Camacho (Knowl. Based Syst., 2024)

Evolving interpretable decision trees for reinforcement learning. - Vinícius G. Costa; Jorge Pérez-Aracil; Sancho Salcedo-Sanz; Carlos Eduardo Pedreira (Artif. Intell., 2024)

Bike sharing and cable car demand forecasting using machine learning and deep learning multivariate time series approaches. - César Peláez-Rodríguez; Jorge Pérez-Aracil; Dusan Fister; Ricardo Torres-Lopez; Sancho Salcedo-Sanz (Expert Syst. Appl., 2024)

TensorCRO: A TensorFlow-based implementation of a multi-method ensemble for optimization. - Alberto Palomo-Alonso; Vinícius G. Costa; Luis M. Moreno-Saavedra; Eugenio Lorente-Ramos; Jorge Pérez-Aracil; Carlos Eduardo Pedreira; Sancho Salcedo-Sanz (Expert Syst. J. Knowl. Eng., 2024)

Go-around occurrence prediction with rule-induction, rule evolution and Machine Learning algorithms. - Cosmin Madalin Marina; Jorge Pérez-Aracil; Eugenio Lorente-Ramos; Carlos Casanova-Mateo; Sancho Salcedo-Sanz (Adv. Eng. Informatics, 2025)

Hybridizing Machine Learning Algorithms With Numerical Models for Accurate Wind Power Forecasting. - Álvaro Abad-Santjago; César Peláez-Rodríguez; Jorge Pérez-Aracil; Julia Sanz-Justo; Carlos Casanova-Mateo; Sancho Salcedo-Sanz (Expert Syst. J. Knowl. Eng., 2025)