Detection of Microcalcifications in Mammographies Based on Linear Pixel Prediction and Support-Vector Machines. - Francisco Martínez-Álvarez; Alicia Troncoso Lora; José Cristóbal Riquelme Santos; Jesús S. Aguilar-Ruiz (CBMS, 2007)

Partitioning-Clustering Techniques Applied to the Electricity Price Time Series. - Francisco Martínez-Álvarez; Alicia Troncoso Lora; José Cristóbal Riquelme Santos; Jesús Manuel Riquelme-Santos (IDEAL, 2007)

Classification of Gene Expression Profiles: Comparison of K-means and Expectation Maximization Algorithms. - Cristina Rubio-Escudero; Francisco Martínez-Álvarez; Rocío Romero-Záliz; Igor Zwir (HIS, 2008)

LBF: A Labeled-Based Forecasting Algorithm and Its Application to Electricity Price Time Series. - Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme; Jesús S. Aguilar-Ruiz (ICDM, 2008)

Improving Time Series Forecasting by Discovering Frequent Episodes in Sequences. - Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme (IDA, 2009)

Quantitative Association Rules Applied to Climatological Time Series Forecasting. - María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme (IDEAL, 2009)

Using Remote Data Mining on LIDAR and Imagery Fusion Data to Develop Land Cover Maps. - Jorge García-Gutiérrez; Francisco Martínez-Álvarez; José C. Riquelme (IEA/AIE (1), 2010)

Pattern recognition to forecast seismic time series. - A. Morales-Esteban; Francisco Martínez-Álvarez; Alicia Troncoso Lora; J. L. Justo; Cristina Rubio-Escudero (Expert Syst. Appl., 2010)

Mining quantitative association rules based on evolutionary computation and its application to atmospheric pollution. - María Martínez-Ballesteros; Alicia Troncoso Lora; Francisco Martínez-Álvarez; José C. Riquelme (Integr. Comput. Aided Eng., 2010)

Pattern Recognition in Biological Time Series. - Francisco Gómez-Vela; Francisco Martínez-Álvarez; Carlos D. Barranco; Norberto Díaz-Díaz; Domingo S. Rodríguez-Baena; Jesús S. Aguilar-Ruiz (CAEPIA, 2011)

Computational Intelligence Techniques for Predicting Earthquakes. - Francisco Martínez-Álvarez; Alicia Troncoso Lora; A. Morales-Esteban; José C. Riquelme (HAIS (2), 2011)

Mining Quantitative Association Rules in Microarray Data using Evolutive Algorithms. - María Martínez-Ballesteros; Cristina Rubio-Escudero; José C. Riquelme; Francisco Martínez-Álvarez (ICAART (1), 2011)

On the use of algorithms to discover motifs in DNA sequences. - Cristina Rubio-Escudero; Francisco Martínez-Álvarez; María Martínez-Ballesteros; José C. Riquelme (ISDA, 2011)

Clustering preprocessing to improve time series forecasting. - Francisco Martínez-Álvarez (AI Commun., 2011)

Discovery of motifs to forecast outlier occurrence in time series. - Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme; Jesús S. Aguilar-Ruiz (Pattern Recognit. Lett., 2011)

An evolutionary algorithm to discover quantitative association rules in multidimensional time series. - María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme (Soft Comput., 2011)

Energy Time Series Forecasting Based on Pattern Sequence Similarity. - Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme; Jesús S. Aguilar-Ruiz (IEEE Trans. Knowl. Data Eng., 2011)

ra A Sensitivity Analysis for Quality Measures of Quantitative Association Rules. - María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme (HAIS, 2013)

Combining pattern sequence similarity with neural networks for forecasting electricity demand time series. - Irena Koprinska; Mashud Rana; Alicia Troncoso Lora; Francisco Martínez-Álvarez (IJCNN, 2013)

A Comparative Study of Machine Learning Regression Methods on LiDAR Data: A Case Study. - Jorge García-Gutiérrez; Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme (SOCO-CISIS-ICEUTE, 2013)

Neural networks to predict earthquakes in Chile. - Jorge Reyes; A. Morales-Esteban; Francisco Martínez-Álvarez (Appl. Soft Comput., 2013)

Determining the best set of seismicity indicators to predict earthquakes. Two case studies: Chile and the Iberian Peninsula. - Francisco Martínez-Álvarez; Jorge Reyes; A. Morales-Esteban; Cristina Rubio-Escudero (Knowl. Based Syst., 2013)

A fast partitioning algorithm using adaptive Mahalanobis clustering with application to seismic zoning. - Antonio Morales-Esteban; Francisco Martínez-Álvarez; Sanja Scitovski; Rudolf Scitovski (Comput. Geosci., 2014)

TriGen: A genetic algorithm to mine triclusters in temporal gene expression data. - David Gutiérrez-Avilés; Cristina Rubio-Escudero; Francisco Martínez-Álvarez; José C. Riquelme (Neurocomputing, 2014)

Selecting the best measures to discover quantitative association rules. - María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme (Neurocomputing, 2014)

Improving Earthquake Prediction with Principal Component Analysis: Application to Chile. - Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; Antonio Morales-Esteban; Jorge Reyes; Alicia Troncoso Lora (HAIS, 2015)

Data Mining for Predicting Traffic Congestion and Its Application to Spanish Data. - Emilio Florido; O. Castaño; Alicia Troncoso; Francisco Martínez-Álvarez (SOCO, 2015)

A Novel Method for Seismogenic Zoning Based on Triclustering: Application to the Iberian Peninsula. - Francisco Martínez-Álvarez; David Gutiérrez-Avilés; Antonio Morales-Esteban; Jorge Reyes; José L. Amaro-Mellado; Cristina Rubio-Escudero (Entropy, 2015)

Detecting precursory patterns to enhance earthquake prediction in Chile. - Emilio Florido; Francisco Martínez-Álvarez; Antonio Morales-Esteban; Jorge Reyes; José Luis Aznarte-Mellado (Comput. Geosci., 2015)

A comparison of machine learning regression techniques for LiDAR-derived estimation of forest variables. - Jorge García-Gutiérrez; Francisco Martínez-Álvarez; Alicia Troncoso Lora; José C. Riquelme (Neurocomputing, 2015)

Automated Spark Clusters Deployment for Big Data with Standalone Applications Integration. - Antonio M. Fernández; José F. Torres; Alicia Troncoso; Francisco Martínez-Álvarez (CAEPIA, 2016)

Finding Electric Energy Consumption Patterns in Big Time Series Data. - Rubén Pérez-Chacón; Ricardo L. Talavera-Llames; Francisco Martínez-Álvarez; Alicia Troncoso Lora (DCAI, 2016)

Short Term Earthquake Prediction in Hindukush Region Using Tree Based Ensemble Learning. - Khawaja M. Asim; Adnan Idris; Francisco Martínez-Álvarez; Talat Iqbal (FIT, 2016)

Passivity Based Control of Cyber Physical Systems Under Zero-Dynamics Attack. - Fawad Hassan; Naeem Iqbal; Francisco Martínez-Álvarez; Khawaja M. Asim (HAIS, 2016)

A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting. - Ricardo L. Talavera-Llames; Rubén Pérez-Chacón; María Martínez-Ballesteros; Alicia Troncoso; Francisco Martínez-Álvarez (HAIS, 2016)

Obtaining optimal quality measures for quantitative association rules. - María Martínez-Ballesteros; Alicia Troncoso; Francisco Martínez-Álvarez; José C. Riquelme (Neurocomputing, 2016)

Improving a multi-objective evolutionary algorithm to discover quantitative association rules. - María Martínez-Ballesteros; Alicia Troncoso Lora; Francisco Martínez-Álvarez; José C. Riquelme (Knowl. Inf. Syst., 2016)

A sensitivity study of seismicity indicators in supervised learning to improve earthquake prediction. - Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; A. Morales-Esteban; Jorge Reyes (Knowl. Based Syst., 2016)

A novel methodology to predict urban traffic congestion with ensemble learning. - Gualberto Asencio-Cortés; Emilio Florido; Alicia Troncoso; Francisco Martínez-Álvarez (Soft Comput., 2016)

Scalable Forecasting Techniques Applied to Big Electricity Time Series. - Antonio Galicia; José F. Torres; Francisco Martínez-Álvarez; Alicia Troncoso (IWANN (2), 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 (IWINAC (2), 2017)

Applications of Computational Intelligence in Time Series. - Francisco Martínez-Álvarez; Alicia Troncoso; Jorge Reyes; María Martínez-Ballesteros; José C. Riquelme (Comput. Intell. Neurosci., 2017)

Temporal analysis of croatian seismogenic zones to improve earthquake magnitude prediction. - Gualberto Asencio-Cortés; Sanja Scitovski; Rudolf Scitovski; Francisco Martínez-Álvarez (Earth Sci. Informatics, 2017)

Using principal component analysis to improve earthquake magnitude prediction in Japan. - Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; A. Morales-Esteban; Jorge Reyes; Alicia Troncoso Lora (Log. J. IGPL, 2017)

Medium-large earthquake magnitude prediction in Tokyo with artificial neural networks. - Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; Alicia Troncoso Lora; A. Morales-Esteban (Neural Comput. Appl., 2017)

PSF: Introduction to R Package for Pattern Sequence Based Forecasting Algorithm. - Neeraj Bokde; Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; Kishore Kulat (R J., 2017)

SmartFD: A Real Big Data Application for Electrical Fraud Detection. - David Gutiérrez-Avilés; J. A. Fábregas; J. Tejedor; Francisco Martínez-Álvarez; Alicia Troncoso; A. Arcos; José C. Riquelme (HAIS, 2018)

Static and Dynamic Ensembles of Neural Networks for Solar Power Forecasting. - Zheng Wang 040; Irena Koprinska; Alicia Troncoso; Francisco Martínez-Álvarez (IJCNN, 2018)

Impact of Auto-evaluation Tests as Part of the Continuous Evaluation in Programming Courses. - Cristina Rubio-Escudero; Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; Alicia Troncoso; José C. Riquelme (SOCO-CISIS-ICEUTE, 2018)

Deep Learning for Big Data Time Series Forecasting Applied to Solar Power. - José F. Torres; Alicia Troncoso; Irena Koprinska; Zheng Wang 040; Francisco Martínez-Álvarez (SOCO-CISIS-ICEUTE, 2018)

Mapping of seismic parameters of the Iberian Peninsula by means of a geographic information system. - José L. Amaro-Mellado; Antonio Morales-Esteban; Francisco Martínez-Álvarez (Central Eur. J. Oper. Res., 2018)

A novel approach to forecast urban surface-level ozone considering heterogeneous locations and limited information. - Álvaro Gómez-Losada; Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; José C. Riquelme (Environ. Model. Softw., 2018)

Earthquake prediction in California using regression algorithms and cloud-based big data infrastructure. - Gualberto Asencio-Cortés; Antonio Morales-Esteban; Xueyi Shang; Francisco Martínez-Álvarez (Comput. Geosci., 2018)

A novel tree-based algorithm to discover seismic patterns in earthquake catalogs. - Emilio Florido; Gualberto Asencio-Cortés; José Luis Aznarte; Cristina Rubio-Escudero; Francisco Martínez-Álvarez (Comput. Geosci., 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)

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)

Big data time series forecasting based on nearest neighbours distributed computing with Spark. - Ricardo L. Talavera-Llames; Rubén Pérez-Chacón; Alicia Troncoso Lora; Francisco Martínez-Álvarez (Knowl. Based Syst., 2018)

A novel imputation methodology for time series based on pattern sequence forecasting. - Neeraj Bokde; Marcus W. Beck; Francisco Martínez-Álvarez; Kishore Kulat (Pattern Recognit. Lett., 2018)

Game-Based Student Response System Applied to a Multidisciplinary Teaching Context. - José Lázaro Amaro-Mellado; Daniel Antón; Macarena Pérez-Suárez; Francisco Martínez-Álvarez (CISIS-ICEUTE, 2019)

Analysis of Student Achievement Scores: A Machine Learning Approach. - Miguel García-Torres; David Becerra-Alonso; Francisco Antonio Gómez Vela; Federico Divina; Isabel López-Cobo; Francisco Martínez-Álvarez (CISIS-ICEUTE, 2019)

Implementation of an Internal Quality Assurance System at Pablo de Olavide University of Seville: Improving Computer Science Students Skills. - Cristina Rubio-Escudero; Francisco Martínez-Álvarez; E. Atencia-Gil; Alicia Troncoso (CISIS-ICEUTE, 2019)

Random Hyper-parameter Search-Based Deep Neural Network for Power Consumption Forecasting. - José F. Torres; David Gutiérrez-Avilés; Alicia Troncoso; Francisco Martínez-Álvarez (IWANN (1), 2019)

Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks. - Antonio M. Fernández; David Gutiérrez-Avilés; Alicia Troncoso; Francisco Martínez-Álvarez (SOCO, 2019)

A Novel Ensemble Method for Electric Vehicle Power Consumption Forecasting: Application to the Spanish System. - Catalina Gomez-Quiles; Gualberto Asencio-Cortés; Adolfo Gastalver-Rubio; Francisco Martínez-Álvarez; Alicia Troncoso; Joan Manresa; José C. Riquelme; Jesús Manuel Riquelme-Santos (IEEE Access, 2019)

Big data solar power forecasting based on deep learning and multiple data sources. - José F. Torres; Alicia Troncoso; Irena Koprinska; Zheng Wang 040; Francisco Martínez-Álvarez (Expert Syst. J. Knowl. Eng., 2019)

Big data and natural disasters: New approaches for spatial and temporal massive data analysis. - Francisco Martínez-Álvarez; A. Morales-Esteban (Comput. Geosci., 2019)

Special issue on Hybrid Artificial Intelligence Systems from HAIS 2016 Conference. - Francisco Martínez-Álvarez; Alicia Troncoso; Héctor Quintián; Emilio Corchado (Neurocomputing, 2019)

MV-kWNN: A novel multivariate and multi-output weighted nearest neighbours algorithm for big data time series forecasting. - Ricardo L. Talavera-Llames; Rubén Pérez-Chacón; Alicia Troncoso; Francisco Martínez-Álvarez (Neurocomputing, 2019)

Multi-step forecasting for big data time series based on ensemble learning. - Antonio Galicia; Ricardo L. Talavera-Llames; Alicia Troncoso Lora; Irena Koprinska; Francisco Martínez-Álvarez (Knowl. Based Syst., 2019)

Use of IT in Project-Based Learning Applied to the Subject Surveying in Civil Engineering. - Oihana Mitxelena-Hoyos; José Lázaro Amaro-Mellado; Francisco Martínez-Álvarez (ICEUTE, 2020)

On the Performance of Deep Learning Models for Time Series Classification in Streaming. - Pedro Lara-Benítez; Manuel Carranza-García; Francisco Martínez-Álvarez; José C. Riquelme (SOCO, 2020)

Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering. - Laura Melgar-García; Maria Teresa Godinho; Rita Espada; David Gutiérrez-Avilés; Isabel Sofia Brito; Francisco Martínez-Álvarez; Alicia Troncoso; Cristina Rubio-Escudero (SOCO, 2020)

A Preliminary Study on Deep Transfer Learning Applied to Image Classification for Small Datasets. - Miguel Ángel Molina; Gualberto Asencio-Cortés; José C. Riquelme; Francisco Martínez-Álvarez (SOCO, 2020)

Port-Hamiltonian Modeling of Multiphysics Systems and Object-Oriented Implementation With the Modelica Language. - Francisco Martínez-Álvarez; Pedro J. Zufiria; Luis José Yebra (IEEE Access, 2020)

Automated Deployment of a Spark Cluster with Machine Learning Algorithm Integration. - Antonio M. Fernández; David Gutiérrez-Avilés; Alicia Troncoso Lora; Francisco Martínez-Álvarez (Big Data Res., 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)

Learning analytics for student modeling in virtual reality training systems: Lineworkers case. - Guillermo Santamaría Bonfil; María-Blanca Ibáñez-Espiga; Miguel Pérez-Ramírez; Gustavo Arroyo-Figueroa; Francisco Martínez-Álvarez (Comput. Educ., 2020)

Big data time series forecasting based on pattern sequence similarity and its application to the electricity demand. - Rubén Pérez-Chacón; Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; Alicia Troncoso Lora (Inf. Sci., 2020)

Advanced Machine Learning and Big Data Analytics in Remote Sensing for Natural Hazards Management. - Francisco Martínez-Álvarez; Dieu Tien Bui (Remote. Sens., 2020)

A novel hybrid GA-PSO framework for mining quantitative association rules. - Fateme Moslehi; Abdorrahman Haeri; Francisco Martínez-Álvarez (Soft Comput., 2020)

Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks. - José F. Torres; M. J. Jiménez-Navarro; Francisco Martínez-Álvarez; Alicia Troncoso (CAEPIA, 2021)

A Model-Based Deep Transfer Learning Algorithm for Phenology Forecasting Using Satellite Imagery. - M. Á. Molina; M. J. Jiménez-Navarro; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (HAIS, 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 (SOCO, 2021)

HLNet: A Novel Hierarchical Deep Neural Network for Time Series Forecasting. - M. J. Jiménez-Navarro; Francisco Martínez-Álvarez; Alicia Troncoso; Gualberto Asencio-Cortés (SOCO, 2021)

Electricity Generation Forecasting in Concentrating Solar-Thermal Power Plants with Ensemble Learning. - A. Melara; José F. Torres; Alicia Troncoso; Francisco Martínez-Álvarez (SOCO, 2021)

Saccade Landing Point Prediction Based on Fine-Grained Learning Method. - Aythami Morales; Francisco Martínez-Álvarez; Russell L. Woods (IEEE Access, 2021)

Deep Learning for Time Series Forecasting: A Survey. - José F. Torres; Dalil Hadjout; Abderrazak Sebaa; Francisco Martínez-Álvarez; Alicia Troncoso (Big Data, 2021)

Mahalanobis clustering for the determination of incidence-magnitude seismic parameters for the Iberian Peninsula and the Republic of Croatia. - Antonio Morales-Esteban; Francisco Martínez-Álvarez; Sanja Scitovski; Rudolf Scitovski (Comput. Geosci., 2021)

Olive Phenology Forecasting Using Information Fusion-Based Imbalanced Preprocessing and Automated Deep Learning. - Andrés Manuel Chacón-Maldonado; Miguel Angel Molina-Cabanillas; Alicia Troncoso; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (HAIS, 2022)

Explainable machine learning for sleep apnea prediction. - A. R. Troncoso-García; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso (KES, 2022)

A novel approach to discover numerical association based on the coronavirus optimization algorithm. - C. Segarra-Martín; María Martínez-Ballesteros; Alicia Troncoso; Francisco Martínez-Álvarez (SAC, 2022)

Explainable Artificial Intelligence for the Electric Vehicle Load Demand Forecasting Problem. - Juan Alberto Gallardo-Gómez; Federico Divina; Alicia Troncoso; Francisco Martínez-Álvarez (SOCO, 2022)

A Cluster-Based Deep Learning Model for Energy Consumption Forecasting in Ethiopia. - Ejigu T. Habtermariam; Kula Kekeba; Alicia Troncoso; Francisco Martínez-Álvarez (SOCO, 2022)

Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection. - Manuel Jesús Jiménez-Navarro; María Martínez-Ballesteros; Isabel Sofia Sousa Brito; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (SOCO, 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)

Special issue SOCO 2019: New trends in soft computing and its application in industrial and environmental problems. - Francisco Martínez-Álvarez; Alicia Troncoso Lora; Héctor Quintián; Emilio Corchado (Neurocomputing, 2022)

A new big data triclustering approach for extracting three-dimensional patterns in precision agriculture. - Laura Melgar-García; David Gutiérrez-Avilés; Maria Teresa Godinho; Rita Espada; Isabel Sofia Brito; Francisco Martínez-Álvarez; Alicia Troncoso; Cristina Rubio-Escudero (Neurocomputing, 2022)

DIAFAN-TL: An instance weighting-based transfer learning algorithm with application to phenology forecasting. - Miguel Angel Molina-Cabanillas; M. J. Jiménez-Navarro; Ricardo Arjona; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (Knowl. Based Syst., 2022)

A deep LSTM network for the Spanish electricity consumption forecasting. - José F. Torres; Francisco Martínez-Álvarez; Alicia Troncoso (Neural Comput. Appl., 2022)

A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia. - E. Tefera; María Martínez-Ballesteros; Alicia Troncoso; Francisco Martínez-Álvarez (HAIS, 2023)

Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning. - M. J. Jiménez-Navarro; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (IWANN (2), 2023)

Predicting Wildfires in the Caribbean Using Multi-source Satellite Data and Deep Learning. - José F. Torres; S. Valencia; Francisco Martínez-Álvarez; N. Hoyos (IWANN (2), 2023)

Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals. - A. R. Troncoso-García; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso Lora (IWANN (1), 2023)

A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal. - Manuel Jesús Jiménez-Navarro; María Martínez-Ballesteros; Isabel Sofia Brito; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (SAC, 2023)

Evolutionary computation to explain deep learning models for time series forecasting. - Angela Troncoso-García; Alicia Troncoso Lora; Francisco Martínez-Álvarez; María Martínez-Ballesteros (SAC, 2023)

Machine Learning Approaches for Predicting Tree Growth Trends Based on Basal Area Increment. - Pablo Casas-Gómez; Francisco Martínez-Álvarez; Alicia Troncoso; Juan Carlos Linares (SOCO (1), 2023)

Olive Oil Fly Population Pest Forecasting Using Explainable Deep Learning. - Andrés Manuel Chacón-Maldonado; A. R. Troncoso-García; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés; Alicia Troncoso (SOCO (2), 2023)

Explaining Learned Patterns in Deep Learning by Association Rules Mining. - M. J. Jiménez-Navarro; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (SOCO (2), 2023)

PHILNet: A novel efficient approach for time series forecasting using deep learning. - M. J. Jiménez-Navarro; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (Inf. Sci., 2023)

A new approach based on association rules to add explainability to time series forecasting models. - A. R. Troncoso-García; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso (Inf. Fusion, 2023)

FS-Studio: An extensive and efficient feature selection experimentation tool for Weka Explorer. - Andrés Manuel Chacón-Maldonado; Gualberto Asencio-Cortés; Francisco Martínez-Álvarez; Alicia Troncoso (SoftwareX, 2023)

A new Apache Spark-based framework for big data streaming forecasting in IoT networks. - Antonio M. Fernández-Gómez; David Gutiérrez-Avilés; Alicia Troncoso; Francisco Martínez-Álvarez (J. Supercomput., 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., 2023)

Explainable hybrid deep learning and Coronavirus Optimization Algorithm for improving evapotranspiration forecasting. - A. R. Troncoso-García; Isabel Brito 001; Alicia Troncoso; Francisco Martínez-Álvarez (Comput. Electron. Agric., 2023)

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. - Laura Melgar-García; Francisco Martínez-Álvarez; Dieu Tien Bui; Alicia Troncoso (Int. J. Digit. Earth, 2023)

A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting. - Manuel Jesús Jiménez-Navarro; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (J. Big Data, 2023)

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 (CAEPIA, 2024)

Ground-Level Ozone Forecasting Using Explainable Machine Learning. - Angela del Robledo Troncoso-García; Manuel Jesús Jiménez-Navarro; Francisco Martínez-Álvarez; Alicia Troncoso (CAEPIA, 2024)

An evolutionary triclustering approach to discover electricity consumption patterns in France. - David Gutiérrez-Avilés; José F. Torres; Francisco Martínez-Álvarez; Jairo Cugliari (SAC, 2024)

Time Series Forecasting in Agriculture: Explainable Deep Learning with Lagged Feature Selection. - A. R. Troncoso-García; M. J. Jiménez-Navarro; Maria Lourdes Linares-Barrera; Isabel Sofia Brito; Francisco Martínez-Álvarez; María Martínez-Ballesteros (SOCO (1), 2024)

Explaining deep learning models for ozone pollution prediction via embedded feature selection. - M. J. Jiménez-Navarro; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Gualberto Asencio-Cortés (Appl. Soft Comput., 2024)

Pattern sequence-based algorithm for multivariate big data time series forecasting: Application to electricity consumption. - Rubén Pérez-Chacón; Gualberto Asencio-Cortés; Alicia Troncoso Lora; Francisco Martínez-Álvarez (Future Gener. Comput. Syst., 2024)

From simple to complex: a sequential method for enhancing time series forecasting with deep learning. - M. J. Jiménez-Navarro; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso; Gualberto Asencio-Cortés (Log. J. IGPL, 2024)

Emerging trends in big data analytics and natural disasters. - Francisco Martínez-Álvarez; Rudolf Scitovski; Cristina Rubio-Escudero; Antonio Morales-Esteban (Comput. Geosci., 2024)

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)

MetaGen: A framework for metaheuristic development and hyperparameter optimization in machine and deep learning. - David Gutiérrez-Avilés; Manuel Jesús Jiménez-Navarro; José Francisco Torres; Francisco Martínez-Álvarez (Neurocomputing, 2025)

A novel approach based on clustering and optimized ensemble deep learning for energy consumption forecasting in Ethiopia. - E. Tefera Habtemariam; María Martínez-Ballesteros; Alicia Troncoso; Francisco Martínez-Álvarez (Neurocomputing, 2025)

A novel explainable AI framework for medical image classification integrating statistical, visual, and rule-based methods. - Naeem Ullah; Florentina Guzmán-Aroca; Francisco Martínez-Álvarez; Ivanoe De Falco; Giovanna Sannino (Medical Image Anal., 2025)

Energy-efficient transfer learning for water consumption forecasting. - A. Gil-Gamboa; José F. Torres; Francisco Martínez-Álvarez; Alicia Troncoso (Sustain. Comput. Informatics Syst., 2025)

A partitioning incremental algorithm using adaptive Mahalanobis fuzzy clustering and identifying the most appropriate partition. - Rudolf Scitovski; Kristian Sabo; Danijel Grahovac; Francisco Martínez-Álvarez; Sime Ungar (Pattern Anal. Appl., 2025)

A New Metric Based on Association Rules to Assess Feature-Attribution Explainability Techniques for Time Series Forecasting. - Angela del Robledo Troncoso-García; María Martínez-Ballesteros; Francisco Martínez-Álvarez; Alicia Troncoso (IEEE Trans. Pattern Anal. Mach. Intell., 2025)