José F. Torres

According to our database, José F. Torres authored at least 21 papers between 2016 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2025

Forecasting basal area increment in forest ecosystems using deep learning: A multi-species analysis in the Himalayas.

Pablo Casas-Gómez, José F. Torres, Juan Carlos Linares, Alicia Troncoso Lora, Francisco Martínez-Álvarez

Ecol. Informatics, 2025

2024

An evolutionary triclustering approach to discover electricity consumption patterns in France.

David Gutiérrez-Avilés, José F. Torres, Francisco Martínez-Álvarez, Jairo Cugliari

Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024

An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines.

Francesc Rodríguez-Díaz, José Francisco Torres, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez

Proceedings of the Advances in Artificial Intelligence, 2024

2023

Electricity consumption forecasting with outliers handling based on clustering and deep learning with application to the Algerian market.

Dalil Hadjout, Abderrazak Sebaa, José F. Torres, Francisco Martínez-Álvarez

Expert Syst. Appl., October, 2023

Predicting Wildfires in the Caribbean Using Multi-source Satellite Data and Deep Learning.

José F. Torres, S. Valencia, Francisco Martínez-Álvarez, N. Hoyos

Proceedings of the Advances in Computational Intelligence, 2023

Explainable Artificial Intelligence for Education: A Real Case of a University Subject Switched to Python.

Laura Melgar-García, Angela Troncoso-García, David Gutiérrez-Avilés, José Francisco Torres, Alicia Troncoso

Proceedings of the International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023), 2023

2022

A deep LSTM network for the Spanish electricity consumption forecasting.

José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso

Neural Comput. Appl., 2022

Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm.

Kien-Trinh Thi Bui, José F. Torres, David Gutiérrez-Avilés, Viet-Ha Nhu, Dieu Tien Bui, Francisco Martínez-Álvarez

Comput. Aided Civ. Infrastructure Eng., 2022

2021

Deep Learning for Time Series Forecasting: A Survey.

José F. Torres, Dalil Hadjout, Abderrazak Sebaa, Francisco Martínez-Álvarez, Alicia Troncoso

Big Data, 2021

Electricity Generation Forecasting in Concentrating Solar-Thermal Power Plants with Ensemble Learning.

A. Melara, José F. Torres, Alicia Troncoso, Francisco Martínez-Álvarez

Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021

Medium-Term Electricity Consumption Forecasting in Algeria Based on Clustering, Deep Learning and Bayesian Optimization Methods.

Dalil Hadjout, José F. Torres, Abderrazak Sebaa, Francisco Martínez-Álvarez

Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021

Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks.

José F. Torres, M. J. Jiménez-Navarro, Francisco Martínez-Álvarez, Alicia Troncoso

Proceedings of the Advances in Artificial Intelligence, 2021

2020

Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model.

Francisco Martínez-Álvarez, Gualberto Asencio-Cortés, José F. Torres, David Gutiérrez-Avilés, Laura Melgar-García, Rubén Pérez-Chacón, Cristina Rubio-Escudero, José C. Riquelme, Alicia Troncoso Lora

Big Data, 2020

2019

Big data solar power forecasting based on deep learning and multiple data sources.

José F. Torres, Alicia Troncoso, Irena Koprinska, Zheng Wang, Francisco Martínez-Álvarez

Expert Syst. J. Knowl. Eng., 2019

Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting.

José F. Torres, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez

Proceedings of the Advances in Computational Intelligence, 2019

2018

A novel spark-based multi-step forecasting algorithm for big data time series.

Antonio Galicia, José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso Lora

Inf. Sci., 2018

A scalable approach based on deep learning for big data time series forecasting.

José F. Torres, Antonio Galicia, Alicia Troncoso Lora, Francisco Martínez-Álvarez

Integr. Comput. Aided Eng., 2018

Deep Learning for Big Data Time Series Forecasting Applied to Solar Power.

José F. Torres, Alicia Troncoso, Irena Koprinska, Zheng Wang, Francisco Martínez-Álvarez

Proceedings of the International Joint Conference SOCO'18-CISIS'18-ICEUTE'18, 2018

2017

Deep Learning-Based Approach for Time Series Forecasting with Application to Electricity Load.

José F. Torres, Antonio M. Fernández, Alicia Troncoso Lora, Francisco Martínez-Álvarez

Proceedings of the Biomedical Applications Based on Natural and Artificial Computing, 2017

Scalable Forecasting Techniques Applied to Big Electricity Time Series.

Antonio Galicia, José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso

Proceedings of the Advances in Computational Intelligence, 2017

2016

Automated Spark Clusters Deployment for Big Data with Standalone Applications Integration.

Antonio M. Fernández, José F. Torres, Alicia Troncoso, Francisco Martínez-Álvarez

Proceedings of the Advances in Artificial Intelligence, 2016