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ORCIDJosé F. Torres
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2020 – today
- 2025
[j9]Pablo Casas-Gómez, José F. Torres, Juan Carlos Linares, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
Forecasting basal area increment in forest ecosystems using deep learning: A multi-species analysis in the Himalayas. Ecol. Informatics 85: 102951 (2025)- 2024
- [c12]Francesc Rodríguez-Díaz
, José Francisco Torres, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez:
An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines. CAEPIA 2024: 121-130 - [c11]David Gutiérrez-Avilés, José F. Torres, Francisco Martínez-Álvarez, Jairo Cugliari:
An evolutionary triclustering approach to discover electricity consumption patterns in France. SAC 2024: 386-394 - 2023
- [j8]Dalil Hadjout, Abderrazak Sebaa, José F. Torres, Francisco Martínez-Álvarez:
Electricity consumption forecasting with outliers handling based on clustering and deep learning with application to the Algerian market. Expert Syst. Appl. 227: 120123 (2023) - [c10]Laura Melgar-García, Angela Troncoso-García, David Gutiérrez-Avilés, José Francisco Torres, Alicia Troncoso:
Explainable Artificial Intelligence for Education: A Real Case of a University Subject Switched to Python. CISIS-ICEUTE 2023: 358-367 - [c9]José F. Torres, S. Valencia, Francisco Martínez-Álvarez, N. Hoyos:
Predicting Wildfires in the Caribbean Using Multi-source Satellite Data and Deep Learning. IWANN (2) 2023: 3-14 - 2022
- [j7]Kien-Trinh Thi Bui, José F. Torres, David Gutiérrez-Avilés, Viet-Ha Nhu, Dieu Tien Bui, Francisco Martínez-Álvarez:
Deformation forecasting of a hydropower dam by hybridizing a long short-term memory deep learning network with the coronavirus optimization algorithm. Comput. Aided Civ. Infrastructure Eng. 37(11): 1368-1386 (2022) - [j6]José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso:
A deep LSTM network for the Spanish electricity consumption forecasting. Neural Comput. Appl. 34(13): 10533-10545 (2022) - 2021
- [j5]José F. Torres, Dalil Hadjout, Abderrazak Sebaa, Francisco Martínez-Álvarez, Alicia Troncoso:
Deep Learning for Time Series Forecasting: A Survey. Big Data 9(1): 3-21 (2021) - [c8]José F. Torres, M. J. Jiménez-Navarro, Francisco Martínez-Álvarez, Alicia Troncoso:
Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks. CAEPIA 2021: 216-225 - [c7]A. Melara, José F. Torres, Alicia Troncoso, Francisco Martínez-Álvarez:
Electricity Generation Forecasting in Concentrating Solar-Thermal Power Plants with Ensemble Learning. SOCO 2021: 665-674 - [c6]Dalil Hadjout, José F. Torres, Abderrazak Sebaa, Francisco Martínez-Álvarez:
Medium-Term Electricity Consumption Forecasting in Algeria Based on Clustering, Deep Learning and Bayesian Optimization Methods. SOCO 2021: 739-748 - 2020
- [j4]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:
Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model. Big Data 8(4): 308-322 (2020) - [i1]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:
Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model. CoRR abs/2003.13633 (2020)
2010 – 2019
- 2019
- [j3]José F. Torres, Alicia Troncoso, Irena Koprinska, Zheng Wang, Francisco Martínez-Álvarez:
Big data solar power forecasting based on deep learning and multiple data sources. Expert Syst. J. Knowl. Eng. 36(4) (2019) - [c5]José F. Torres, David Gutiérrez-Avilés, Alicia Troncoso, Francisco Martínez-Álvarez:
Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting. IWANN (1) 2019: 259-269 - 2018
- [j2]José F. Torres, Antonio Galicia, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
A scalable approach based on deep learning for big data time series forecasting. Integr. Comput. Aided Eng. 25(4): 335-348 (2018) - [j1]Antonio Galicia, José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso Lora:
A novel spark-based multi-step forecasting algorithm for big data time series. Inf. Sci. 467: 800-818 (2018) - [c4]José F. Torres, Alicia Troncoso, Irena Koprinska, Zheng Wang, Francisco Martínez-Álvarez:
Deep Learning for Big Data Time Series Forecasting Applied to Solar Power. SOCO-CISIS-ICEUTE 2018: 123-133 - 2017
- [c3]Antonio Galicia, José F. Torres, Francisco Martínez-Álvarez, Alicia Troncoso:
Scalable Forecasting Techniques Applied to Big Electricity Time Series. IWANN (2) 2017: 165-175 - [c2]José F. Torres, Antonio M. Fernández, Alicia Troncoso Lora, Francisco Martínez-Álvarez:
Deep Learning-Based Approach for Time Series Forecasting with Application to Electricity Load. IWINAC (2) 2017: 203-212 - 2016
- [c1]Antonio M. Fernández, José F. Torres, Alicia Troncoso, Francisco Martínez-Álvarez:
Automated Spark Clusters Deployment for Big Data with Standalone Applications Integration. CAEPIA 2016: 150-159
Coauthor Index
aka: Alicia Troncoso
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