Publications

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2024

D. Gutiérrez-Avilés and J. F. Torres and F. Martínez-Álvarez and J. Cugliari

An evolutionary triclustering approach to discover electricity consumption patterns in France (Conference)

SAC 39th Annual ACM Symposium on Applied Computing, 2024.

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

R. Pérez-Chacón and G. Asencio-Cortés and A. Troncoso and F. Martínez-Álvarez

Pattern sequence-based algorithm for multivariate big data time series forecasting: Application to electricity consumption (Journal Article)

Future Generation Computer Systems, 154 , pp. 397-412, 2024.

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

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)

F. Martínez-Álvarez and R. Scitovski and C. Rubio-Escudero and A. Morales-Esteban

Emerging trends in big data analytics and natural disasters (Editorial) (Journal Article)

Computers and Geosciences, 182 , pp. 105465, 2024.

(Links | BibTeX | Tags: big data, natural disasters, time series)

2023

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)

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)

D. Azzouguer and A. Sebaa and D. Hadjout and F. Martínez-Álvarez

Fraud Detection of Electricity Consumption using Robust Exponential and Holt-Winters Smoothing method (Conference)

IEEE International Conference on Advanced Systems and Emergent Technologies, 2023.

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

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

A new approach based on association rules to add explainability to time series forecasting models (Journal Article)

Information Fusion, 94 , pp. 169-180, 2023.

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

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)

P. Jiménez-Herrera and L. Melgar-García and G. Asencio-Cortés and A. Troncoso

Streaming big time series forecasting based on nearest similar patterns with application to energy consumption (Journal Article)

Logic Journal of the IGPL, 31 (2), pp. 255-270, 2023.

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

L. Melgar-García and D. Gutiérrez-Avilés and C. Rubio-Escudero and A.Troncoso

Identifying novelties and anomalies for incremental learning in streaming time series forecasting (Journal Article)

Engineering Applications of Artificial Intelligence, 123 , pp. 106326, 2023.

(Links | BibTeX | Tags: energy, IoT, time series)

L. Melgar-García and D. Gutiérrez-Avilés and C. Rubio-Escudero and A. Troncoso

A novel distributed forecasting method based on information fusion and incremental learning for streaming time series (Journal Article)

Information Fusion, 95 , pp. 163-173, 2023.

(Links | BibTeX | Tags: energy, IoT, 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)

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, 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)

P. Casas-Gómez and F. Martínez-Álvarez and A. Troncoso and J. C. Linares-Calderón

Machine Learning Approaches for Predicting Tree Growth Trends based on Basal Area Increment (Conference)

SOCO 18th International Conference on Soft Computing Models in Industrial and Environmental Applications, Lecture Notes in Networks and Systems 2023.

(BibTeX | Tags: time series)

2022

M. Á. Molina and M. J. Jiménez-Navarro and R. Arjona and F. Mártinez-Álvarez and G. Asencio-Cortés

DIAFAN-TL: An instance weighting-based transfer learning algorithm with application to phenology forecasting (Journal Article)

Knowledge-Based Systems, 254 , pp. 109644, 2022.

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

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)

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)

A. Gómez-Losada and G. Asencio-Cortés and N. Duch-Brown

Automatic Eligibility of Sellers in an Online Marketplace: A Case Study of Amazon Algorithm (Journal Article)

Information, 13 (44), pp. 1–16, 2022.

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

M.A. Castán-Lascorz and P. Jiménez-Herrera and A. Troncoso and G. Asencio-Cortés

A new hybrid method for predicting univariate and multivariate time series based on pattern forecasting (Journal Article)

Information Sciences, 586 , pp. 611–627, 2022.

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

G. Velázquez and F. Morales and M. García-Torres and F. Gómez-Vela and F. Divina and J.L. Vázquez Noguera and F. Daumas-Ladouce and C. Ayala and D. Pinto-Roaand P. Gardel-Sotomayor

Distribution level Electric current consumption and meteorological data set of the East region of Paraguay (Journal Article)

Data in Brief, 40 , pp. 107699, 2022.

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

J. A. Gallardo-Gómez and F. Divina and A. Troncoso and F. Martínez-Álvarez

Explainable Artificial Intelligence for the Electric Vehicle Load Demand Forecasting Problem (Conference)

SOCO 17th International Conference on Soft Computing Models in Industrial and Environmental Applications, Advances in Intelligent Systems and Computing 2022.

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

F. Morales and M. García-Torres and G. Velázquez and F. Daumas-Ladouce and P. Gardel-Sotomayor and F. Gómez-Vela and F. Divina and J. L. Vázquez Noguera and C. Sauer Ayala and D. Pinto-Roa

Analysis of Electric Energy Consumption Profiles Using a Machine Learning Approach: A Paraguayan Case Study (Journal Article)

Electronics, 11 (2), pp. 267, 2022.

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

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)

L. Melgar-García and D. Gutiérrez-Avilés and C. Rubio-Escudero and A. Troncoso

Nearest neighbors with incremental learning for real-time forecasting of electricity demand (Conference)

IEEE International Conference on Data Mining Workshops, 2022.

(Links | BibTeX | Tags: energy, IoT, time series)

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)

J. Roiz-Pagador and A. M. Chacon-Maldonado and R. Ruiz and G. Asencio-Cortes

Earthquake Prediction in California using Feature Selection techniques (Conference)

SOCO 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, Advances in Intelligent Systems and Computing 2021.

(Links | BibTeX | Tags: feature selection, natural disasters, time series)

L. Melgar-García and D. Gutiérrez-Avilés and C. Rubio-Escudero and A. Troncoso

Nearest neighbours-based forecasting for electricity demand time series in streaming (Conference)

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

(Abstract | BibTeX | Tags: IoT, time series)

J. A. Gallardo and M. García-Torres and F. Gómez-Vela and F. Morales and F. Divina and D. Becerra-Alonso and G. Velázquez and F. Daumas-Ladouce and J. L. Vázquez Noguera and C. Ayala Sauer

Forecasting Electricity Consumption Data from Paraguay Using a Machine Learning Approach (Conference)

SOCO 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 1401 , Advances in Intelligent Systems and Computing 2021.

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

2020

P. Jiménez-Herrera and L. Melgar-García and G. Asencio-Cortés and A. Troncoso

A New Forecasting Algorithm Based on Neighbors for Streaming Electricity Time Series (Conference)

HAIS 15th International Conference on Hybrid Artificial Intelligence Systems, Lecture Notes in Computer Science 2020.

(Links | BibTeX | Tags: big data, energy, IoT, time series)

Y. Lin and I. Koprinska and M. Rana and A. Troncoso

Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning (Conference)

ICANN 29th International Conference on Artificial Neural Networks, Lecture Notes in Computer Science 2020.

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

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)

R. Pérez-Chacón and G. Asencio-Cortés and F. Martínez-Álvarez and A. Troncoso

Big data time series forecasting based on pattern sequence similarity and its application to the electricity demand (Journal Article)

Information Sciences, 540 , pp. 160-174, 2020.

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

146 entries « 1 of 3 »