Publications

Show all

2024

C. G. García-Soto and J. F. Torres and M. A. Zamora-Izquierdo and J. Palma and A. Troncoso

Water consumption time series forecasting in urban centers using deep neural networks (Journal Article)

Applied Water Science, 14 , pp. 1-14, 2024.

(Abstract | Links | BibTeX | Tags: deep learning, forecasting, time series)

2023

A. R. Troncoso-García and I. S. Brito and A. Troncoso and F. Mártinez-Álvarez

Explainable hybrid deep learning and Coronavirus Optimization Algorithm for improving evapotranspiration forecasting (Journal Article)

Computers and Electronics in Agriculture, 215 , pp. 108387, 2023.

(Abstract | Links | BibTeX | Tags: deep learning, forecasting, precision agriculture, XAI)

D. Hadjout and A. Sebaa and J. F. Torres and F. Mártinez-Álvarez

Electricity consumption forecasting with outliers handling based on clustering and deep learning with application to the Algerian market (Journal Article)

Expert Systems with Applications, 227 , pp. 120123, 2023.

(Abstract | Links | BibTeX | Tags: clustering, deep learning, energy, time series)

J. F. Torres and S. Valencia and F. Martínez-Álvarez and N. Hoyos

Predicting Wildfires in the Caribbean Using Multi-source Satellite Data and Deep Learning (Conference)

IWANN 17th International Work-Conference on Artificial Neural Networks, 14135 , Lecture Notes in Computer Science 2023.

(Links | BibTeX | Tags: deep learning, natural disasters, time series)

A. R. Troncoso-García and M. Martínez-Ballesteros and F. Martínez-Álvarez and A. Troncoso

Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals (Conference)

IWANN 17th International Work-Conference on Artificial Neural Networks, 14134 , Lecture Notes in Computer Science 2023.

(Links | BibTeX | Tags: deep learning, forecasting, time series)

M. J. Jiménez-Navarro and M. Martínez-Ballesteros and F. Martínez-Álvarez and G. Asencio-Cortés

Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning (Conference)

IWANN 17th International Work-Conference on Artificial Neural Networks, 14135 , Lecture Notes in Computer Science 2023.

(Links | BibTeX | Tags: deep learning, feature selection, time series)

P. García-Bringas and H. Pérez-García and F. J. Martínez de Pisón and F. Martínez-Álvarez and A. Troncoso and Á. Herrero and J. L. Calvo-Rolle and H. Quintián and E. Corchado

Proceedings of the 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) Salamanca, Spain, September 5-7, 2023, volume 1 (Proceeding)

Springer, 749 , 2023, ISBN: 978-3-031-42529-5.

(Links | BibTeX | Tags: big data, clustering, deep learning, IoT)

P. García-Bringas and H. Pérez-García and F. J. Martínez de Pisón and F. Martínez-Álvarez and A. Troncoso and Á. Herrero and J. L. Calvo-Rolle and H. Quintián and E. Corchado

Proceedings of the 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023) Salamanca, Spain, September 5-7, 2023, volume 2 (Proceeding)

Springer, 750 , 2023, ISBN: 978-3-031-42536-3.

(Links | BibTeX | Tags: big data, clustering, deep learning, IoT)

P. García-Bringas and H. Pérez-García and F. J. Martínez de Pisón and F. Martínez-Álvarez and A. Troncoso and Á. Herrero and J. L. Calvo-Rolle and H. Quintián and E. Corchado

Proceedings of the 18th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2023) Salamanca, Spain, September 5-7, 2023 (Proceeding)

Springer, 14001 , 2023, ISBN: 978-3-031-40725-3.

(Links | BibTeX | Tags: big data, clustering, deep learning, IoT)

A. Vellinger and J. F. Torres and F. Divina and W. Vanhoof

Neuroevolutionary Transfer Learning for Time Series Forecasting (Conference)

SOCO International Conference on Soft Computing Models in Industrial and Environmental Applications, 749 , Lecture Notes in Networks and Systems 2023.

(Links | BibTeX | Tags: deep learning, forecasting, time series, transfer learning)

M. J. Jiménez-Navarro and M. Martínez-Ballesteros and F. Martínez-Álvarez and G. Asencio-Cortés

A New Deep Learning Architecture with Inductive Bias Balance for Oil Temperature Forecasting (Journal Article)

Journal of Big Data, 10 , pp. 80, 2023.

(Abstract | Links | BibTeX | Tags: deep learning, time series)

M. J. Jiménez-Navarro and M. Martínez-Ballesteros and F. Martínez-Álvarez and G. Asencio-Cortés

PHILNet: A Novel Efficient Approach for Time Series Forecasting using Deep Learning (Journal Article)

Information Sciences, 632 , pp. 815-832, 2023.

(Abstract | Links | BibTeX | Tags: deep learning, time series)

E. T. Habtemariam and K. Kekeba and M. Martínez-Ballesteros and F. Mártinez-Álvarez

A Bayesian Optimization-Based LSTM Model for Wind Power Forecasting in the Adama District, Ethiopia (Journal Article)

Energies, 16 , pp. 2317, 2023.

(Abstract | Links | BibTeX | Tags: deep learning, time series)

M. J. Jiménez-Navarro and M. Martínez-Ballesteros and F. Mártinez-Álvarez and A. Troncoso and G. Asencio-Cortés

From Simple to Complex: A Sequential Method for Enhancing Time Series Forecasting with Deep Learning (Journal Article)

Logic Journal of the IGPL, in press , 2023.

(Abstract | BibTeX | Tags: deep learning, time series)

A. R. Troncoso-García and m. Martínez-Ballesteros and F. Martínez-Álvarez and A. Troncoso

Evolutionary computation to explain deep learning models for time series forecasting (Conference)

SAC 38th Annual ACM Symposium on Applied Computing, 2023.

(Links | BibTeX | Tags: deep learning, time series, XAI)

A. R. Troncoso-García and M. Martínez-Ballesteros and F. Martínez-Álvarez and A. Troncoso

Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals (Conference)

IWANN International Work-conference on Artificial Intelligence, Lecture Notes in Computer Science 2023.

(BibTeX | Tags: deep learning, feature selection, time series)

L. Melgar-García, M. Hosseini and A. Troncoso

Identification of anomalies in urban sound data with Autoencoders (Conference)

HAIS 18th International Conference on Hybrid Artificial Intelligence Systems, Lecture Notes in Computer Science 2023.

(BibTeX | Tags: deep learning, IoT, time series)

E. Tefera and A. Troncoso and M. Martínez Ballesteros and F. Martínez-Álvarez

A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia (Conference)

HAIS 18th International Conference on Hybrid Artificial Intelligence Systems, Lecture Notes in Computer Science 2023.

(BibTeX | Tags: deep learning, energy, time series)

M. J. Jiménez-Navarro and M. Martínez-Ballesteros and I. S. Brito and F. Martínez-Álvarez and G. Asencio-Cortés

A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal (Conference)

SAC 38th Annual ACM Symposium on Applied Computing, 2023.

(Abstract | Links | BibTeX | Tags: deep learning, precision agriculture, time series)

L. Melgar-García and F. Martínez-Álvarez and D. T. Bui and A. Troncoso

A novel semantic segmentation approach based on U-Net, WU-Net, and U-Net++ deep learning for predicting areas sensitive to pluvial flood at tropical area (Journal Article)

International Journal of Digital Earth, 16 (1), pp. 3661-3679, 2023.

(Links | BibTeX | Tags: deep learning, natural disasters)

2022

A. M. Chacón-Maldonado and M. A. Molina and A. Troncoso and F. Martínez-Álvarez and G. Asencio-Cortés

Olive Phenology Forecasting Using Information Fusion-Based Imbalanced Preprocessing and Automated Deep Learning (Conference)

HAIS 17th International Conference on Hybrid Artificial Intelligence Systems, Lecture Notes in Computer Science 2022.

(Links | BibTeX | Tags: deep learning, pattern recognition, time series)

A. R. Troncoso-García and M. Martínez-Ballesteros and F. Martínez-Álvarez and A. Troncoso

Explainable machine learning for sleep apnea prediction (Conference)

KES International Conference on Knowledge Based and Intelligent information and Engineering Systems, 2022.

(Abstract | Links | BibTeX | Tags: association rules, deep learning, time series, XAI)

P. García-Bringas and H. Pérez-García and F. J. Martínez de Pisón and J. R. Villar-Flecha and A. Troncoso and E. A. de la Cal and Á. Herrero and F. Martínez-Álvarez and G. Psaila and H. Quintián and E. Corchado

Proceedings of the 17th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2022) Salamanca, Spain, September 5-7, 2022 (Proceeding)

Springer, 13469 , 2022, ISBN: 978-3-031-15470-6.

(Links | BibTeX | Tags: big data, clustering, deep learning, IoT)

P. García-Bringas and H. Pérez-García and F. J. Martínez de Pisón and J. R. Villar-Flecha and A. Troncoso and E. A. de la Cal and Á. Herrero and F. Martínez-Álvarez and G. Psaila and H. Quintián and E. Corchado

Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022) Salamanca, Spain, September 5-7, 2022 (Proceeding)

Springer, 531 , 2022, ISBN: 978-3-031-18050-7.

(Links | BibTeX | Tags: big data, clustering, deep learning, IoT)

P. García-Bringas and H. Pérez-García and F. J. Martínez de Pisón and J. R. Villar-Flecha and A. Troncoso and E. A. de la Cal and Á. Herrero and F. Martínez-Álvarez and G. Psaila and H. Quintián and E. Corchado

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). Salamanca, Spain, September 5-7, 2022 (Proceeding)

Springer, 532 , 2022, ISBN: 978-3-031-18409-3.

(Links | BibTeX | Tags: big data, deep learning)

D. Hadjout and J. F. Torres and A. Troncoso and A. Sebaa and F. Martínez-Álvarez

Electricity consumption forecasting based on ensemble deep learning with application to the Algerian market (Journal Article)

Energy, 243 , pp. 123060, 2022.

(Abstract | Links | BibTeX | Tags: deep learning, energy, time series)

J. F. Torres and F. Martínez-Álvarez and A. Troncoso

A deep LSTM network for the Spanish electricity consumption forecasting (Journal Article)

Neural Computing and Applications, 34 , pp. 10533-10545, 2022.

(Abstract | Links | BibTeX | Tags: deep learning, energy)

E. T. Habtermariam and K. Kekeba and A. Troncoso and F. Martínez-Álvarez

A Cluster-Based Deep Learning Model for Energy Consumption Forecasting in Ethiopia (Conference)

SOCO 17th International Conference on Soft Computing Models in Industrial and Environmental Applications , 531 , Lecture Notes in Networks and Systems 2022.

(Links | BibTeX | Tags: deep learning, energy, pattern recognition, time series)

M. J. Jiménez-Navarro and M. Martínez-Ballesteros and I. S. Sousa Brito and F. Martínez-Álvarez and G. Asencio-Cortés

Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection (Conference)

SOCO 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, 531 , Lecture Notes in Networks Systems 2022.

(Links | BibTeX | Tags: deep learning, feature selection)

2021

K.-T. T. Bui and J. F. Torres and D. Gutiérrez-Avilés and V. H. Nhu and F. Martínez-Álvarez and D. T. Bui

Deformation forecasting of a hydropower dam by hybridizing a Long Short-Term Memory deep learning network with the Coronavirus Optimization Algorithm (Journal Article)

Computer-Aided Civil and Infrastructure Engineering, 37 , pp. 1368-1386, 2021.

(Abstract | Links | BibTeX | Tags: deep learning, time series)

J. F. Torres and M. J. Jiménez-Navarro and F. Martínez-Álvarez and A. Troncoso

Electricity consumption time series forecasting using Temporal Convolutional Networks (Conference)

CAEPIA Conference of the Spanish Association for Artificial Intelligence , Lecture Notes in Artificial Intelligence 2021.

(BibTeX | Tags: deep learning, time series)

A. Melara and J. F. Torres and A. Troncoso and F. Martínez-Álvarez

Electricity Generation Forecasting in Concentrating Solar-Thermal Power Plants with Ensemble Learning (Conference)

SOCO International Conference on Soft Computing Models in Industrial and Environmental Applications, 1401 , Advances in Intelligent Systems and Computing 2021.

(Links | BibTeX | Tags: deep learning, energy, time series)

D. Hadjout and J. F. Torres and A. Sebaa and F. Martínez-Álvarez

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

SOCO International Conference on Soft Computing Models in Industrial and Environmental Applications, 1401 , Advances in Intelligent Systems and Computing 2021.

(Links | BibTeX | Tags: deep learning, energy, time series)

M. J. Jiménez-Navarro and F. Martínez-Álvarez and A. Troncoso and G. Asencio-Cortés

HLNet: A Novel Hierarchical Deep Neural Network for Time Series Forecasting (Conference)

SOCO International Conference on Soft Computing Models in Industrial and Environmental Applications, 1401 , Advances in Intelligent Systems and Computing 2021.

(Links | BibTeX | Tags: deep learning, time series)

M. A. Molina and M. J. Jiménez-Navarro and F. Martínez-Álvarez and G. Asencio-Cortés

A Model-Based Deep Transfer Learning Algorithm for Phenology Forecasting Using Satellite Imagery (Conference)

HAIS 16th International Conference on Hybrid Artificial Intelligence Systems, 12886 , Lecture Notes in Computer Science 2021.

(Links | BibTeX | Tags: deep learning, time series)

J. F. Torres and D. Hadjout and A. Sebaa and F. Martínez-Álvarez and A. Troncoso

Deep Learning for Time Series Forecasting: A Survey (Journal Article)

Big Data, 9 (1), pp. 3-21, 2021.

(Abstract | Links | BibTeX | Tags: big data, deep learning, time series)

R. Parra and V. Ojeda and J.L. Vázquez Noguera and M. García-Torres and J.C. Mello-Román and C. Villalba and J. Facon and F. Divina and O. Cardozo and V. Castillo

A Trust-Based Methodology to Evaluate Deep Learning Models for Automatic Diagnosis of Ocular Toxoplasmosis from Fundus Images (Journal Article)

Diagnostics, 11 (11), pp. 1951, 2021.

(Links | BibTeX | Tags: bioinformatics, deep learning, pattern recognition)

J. Ayala and M. García-Torres and J.L. Vázquez Noguera and F. Gómez-Vela and F. Divina

Technical analysis strategy optimization using a machine learning approach in stock market indices (Journal Article)

Knowledge-Based Systems, pp. 107119, 2021.

(Links | BibTeX | Tags: deep learning, pattern recognition)

2020

F. Divina and J. F. Torres and M. García-Torres and F. Martínez-Álvarez and A. Troncoso

Hybridizing deep learning and neuroevolution: Application to the Spanish short-term electric energy consumption forecasting (Journal Article)

Applied Sciences, 10 (16), pp. 5487, 2020.

(Abstract | Links | BibTeX | Tags: big data, deep learning, energy, time series)

F. Martínez-Álvarez and G. Asencio-Cortés and J. F. Torres and D. Gutiérrez-Avilés and L. Melgar-García and R. Pérez-Chacón and C. Rubio-Escudero and A. Troncoso and J. C. Riquelme

Coronavirus Optimization Algorithm: A bioinspired metaheuristic based on the COVID-19 propagation model (Journal Article)

Big Data, 8 (4), pp. 308-322, 2020.

(Abstract | Links | BibTeX | Tags: big data, deep learning, energy, time series)

M. A. Molina and G. Asencio-Cortés and J. C. Riquelme and F. Martínez-Álvarez

A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets (Conference)

SOCO 15th International Conference on Soft Computing Models in Industrial and Environmental Applications, 1268 , Advances in Intelligent Systems and Computing 2020.

(Links | BibTeX | Tags: deep learning, pattern recognition, transfer learning)

2019

J. F. Torres and D. Gutiérrez-Avilés and A. Troncoso and F. Martínez-Álvarez

Random Hyper-Parameter Search-Based Deep Neural Network for Power Consumption Forecasting (Conference)

IWANN 15th International Work-Conference on Artificial Neural Networks, 11506 , Lecture Notes in Computer Science 2019.

(Links | BibTeX | Tags: deep learning, energy, time series)

J. F. Torres and A. Troncoso and I. Koprinska and Z. Wang and F. Martínez-Álvarez

Big data solar power forecasting based on deep learning and multiple data sources (Journal Article)

Expert Systems, 36 , pp. id12394, 2019.

(Links | BibTeX | Tags: deep learning, energy, time series)

2018

J. F. Torres and A. Galicia and A. Troncoso and F. Martínez-Álvarez

A scalable approach based on deep learning for big data time series forecasting (Journal Article)

Integrated Computer-Aided Engineering, 25 (4), pp. 335-348, 2018.

(Abstract | Links | BibTeX | Tags: deep learning, energy, time series)

J. F. Torres and A. Troncoso and I. Koprinska and Z. Wang and F. Martínez-Álvarez

Deep learning for big data time series forecasting applied to solar power (Conference)

SOCO 13th International Conference on Soft Computing Models in Industrial and Environmental Applications, Advances in Intelligent Systems and Computing 2018.

(Links | BibTeX | Tags: deep learning, energy, time series)

2017

J. F. Torres and A. M. Fernández and A. Troncoso and F. Martínez-Álvarez

Deep Learning - Based Approach for Time Series Forecasting with Application to Electricity Load (Conference)

IWINAC International Work-Conference on the Interplay Between Natural and Artificial Computation, Lecture Notes in computer Science 2017.

(Abstract | Links | BibTeX | Tags: deep learning, energy, time series)