Electricity Market Price Forecasting: Neural Networks versus Weighted-Distance k Nearest Neighbours. - Alicia Troncoso Lora; José Cristóbal Riquelme Santos; Jesús Manuel Riquelme-Santos; José Luís Martínez Ramos; Antonio Gómez Expósito (DEXA, 2002)

A Comparison of Two Techniques for Next-Day Electricity Price Forecasting. - Alicia Troncoso Lora; Jesús Manuel Riquelme-Santos; José Cristóbal Riquelme Santos; Antonio Gómez Expósito; José Luís Martínez Ramos (IDEAL, 2002)

Application of Evolutionary Computation Techniques to the Optimal Short-Term Scheduling of the Electrical Energy Production. - Alicia Troncoso Lora; José Cristóbal Riquelme Santos; José Luís Martínez Ramos; Jesús Manuel Riquelme-Santos; Antonio Gómez Expósito (CAEPIA, 2003)

Time-Series Prediction: Application to the Short-Term Electric Energy Demand. - Alicia Troncoso Lora; Jesús Manuel Riquelme-Santos; José Cristóbal Riquelme Santos; Antonio Gómez Expósito; José Luís Martínez Ramos (CAEPIA, 2003)

Influence of kNN-Based Load Forecasting Errors on Optimal Energy Production. - Alicia Troncoso Lora; José Cristóbal Riquelme Santos; José Luís Martínez Ramos; Jesús Manuel Riquelme-Santos; Antonio Gómez Expósito (EPIA, 2003)

Advances in optimization and prediction techniques: Real-world applications. - Alicia Troncoso Lora (AI Commun., 2006)

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)

Biclusters Evaluation Based on Shifting and Scaling Patterns. - Juan A. Nepomuceno; Alicia Troncoso Lora; Jesús S. Aguilar-Ruiz; Jorge García-Gutiérrez (IDEAL, 2007)

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)

Evolutionary techniques applied to the optimal short-term scheduling of the electrical energy production. - Alicia Troncoso Lora; José Cristóbal Riquelme Santos; Jesús S. Aguilar-Ruiz; Jesús Manuel Riquelme-Santos (Eur. J. Oper. Res., 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)

An Overlapping Control-Biclustering Algorithm from Gene Expression Data - Juan A. Nepomuceno; Alicia Troncoso Lora; Jesús S. Aguilar-Ruiz (ISDA, 2009)

A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms. - Juan A. Nepomuceno; Alicia Troncoso Lora; Jesús S. Aguilar-Ruiz (PRIB, 2009)

Correlation-Based Scatter Search for Discovering Biclusters from Gene Expression Data. - Juan A. Nepomuceno; Alicia Troncoso Lora; Jesús S. Aguilar-Ruiz (EvoBIO, 2010)

Evolutionary metaheuristic for biclustering based on linear correlations among genes. - Juan A. Nepomuceno; Alicia Troncoso Lora; Jesús S. Aguilar-Ruiz (SAC, 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)

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

Inferring gene coexpression networks with Biclustering based on Scatter Search. - Juan A. Nepomuceno; Alicia Troncoso Lora; Jesús S. Aguilar-Ruiz (ISDA, 2011)

A local search in Scatter Search for improving Biclusters. - Juan A. Nepomuceno; Alicia Troncoso Lora; Jesús S. Aguilar-Ruiz (NaBIC, 2011)

Biclustering of Gene Expression Data by Correlation-Based Scatter Search. - Juan A. Nepomuceno; Alicia Troncoso Lora; Jesús S. Aguilar-Ruiz (BioData Min., 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)

A Kernel for Time Series Classification: Application to Atmospheric Pollutants. - Marta Arias; Alicia Troncoso Lora; José C. Riquelme (SOCO, 2012)

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)

Forecasting hourly electricity load profile using neural networks. - Mashud Rana; Irena Koprinska; Alicia Troncoso Lora (IJCNN, 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)

Including Content-Based Methods in Peer-Assessment of Open-Response Questions. - Oscar Luaces; Jorge Díez 001; Amparo Alonso-Betanzos; Alicia Troncoso; Antonio Bahamonde (ICDM Workshops, 2015)

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

Scatter search-based identification of local patterns with positive and negative correlations in gene expression data. - Juan A. Nepomuceno; Alicia Troncoso; Jesús S. Aguilar-Ruiz (Appl. Soft Comput., 2015)

Integrating biological knowledge based on functional annotations for biclustering of gene expression data. - Juan A. Nepomuceno; Alicia Troncoso Lora; Isabel A. Nepomuceno-Chamorro; Jesús S. Aguilar-Ruiz (Comput. Methods Programs Biomed., 2015)

Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets. - María Martínez-Ballesteros; Jaume Bacardit; Alicia Troncoso Lora; José C. Riquelme (Integr. Comput. Aided Eng., 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)

A multi-scale smoothing kernel for measuring time-series similarity. - Alicia Troncoso Lora; Marta Arias; José C. Riquelme (Neurocomputing, 2015)

A factorization approach to evaluate open-response assignments in MOOCs using preference learning on peer assessments. - Oscar Luaces; Jorge Díez 001; Amparo Alonso-Betanzos; Alicia Troncoso Lora; Antonio Bahamonde (Knowl. Based Syst., 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)

Biclustering of Gene Expression Data Based on SimUI Semantic Similarity Measure. - Juan A. Nepomuceno; Alicia Troncoso; Isabel A. Nepomuceno-Chamorro; Jesús S. Aguilar-Ruiz (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)

Extended Weighted Nearest Neighbor for Electricity Load Forecasting. - Mashud Rana; Irena Koprinska; Alicia Troncoso; Vassilios G. Agelidis (ICANN (2), 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 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)

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)

Content-based methods in peer assessment of open-response questions to grade students as authors and as graders. - Oscar Luaces; Jorge Díez 001; Amparo Alonso-Betanzos; Alicia Troncoso; Antonio Bahamonde (Knowl. Based Syst., 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)

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)

Pairwise gene GO-based measures for biclustering of high-dimensional expression data. - Juan A. Nepomuceno; Alicia Troncoso; Isabel A. Nepomuceno-Chamorro; Jesús S. Aguilar-Ruiz (BioData Min., 2018)

Time series clustering based on the characterisation of segment typologies. - David Guijo-Rubio; Antonio Manuel Durán-Rosal; Pedro Antonio Gutiérrez; Alicia Troncoso; César Hervás-Martínez (CoRR, 2018)

Imbalanced classification techniques for monsoon forecasting based on a new climatic time series. - Alicia Troncoso Lora; P. Ribera; Gualberto Asencio-Cortés; Inmaculada Vega; D. Gallego (Environ. Model. Softw., 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)

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)

Pattern Sequence Neural Network for Solar Power Forecasting. - Yang Lin; Irena Koprinska; Mashud Rana; Alicia Troncoso (ICONIP (5), 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)

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)

A New Forecasting Algorithm Based on Neighbors for Streaming Electricity Time Series. - P. Jiménez-Herrera; Laura Melgar-García; Gualberto Asencio-Cortés; Alicia Troncoso (HAIS, 2020)

Solar Power Forecasting Based on Pattern Sequence Similarity and Meta-learning. - Yang Lin; Irena Koprinska; Mashud Rana; Alicia Troncoso (ICANN (1), 2020)

High-content screening images streaming analysis using the STriGen methodology. - Laura Melgar-García; David Gutiérrez-Avilés; Cristina Rubio-Escudero; Alicia Troncoso (SAC, 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)

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)

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)

Nearest Neighbors-Based Forecasting for Electricity Demand Time Series in Streaming. - Laura Melgar-García; David Gutiérrez-Avilés; Cristina Rubio-Escudero; Alicia Troncoso Lora (CAEPIA, 2021)

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

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

Discovering three-dimensional patterns in real-time from data streams: An online triclustering approach. - Laura Melgar-García; David Gutiérrez-Avilés; Cristina Rubio-Escudero; Alicia Troncoso (Inf. Sci., 2021)

Time-Series Clustering Based on the Characterization of Segment Typologies. - David Guijo-Rubio; Antonio Manuel Durán-Rosal; Pedro Antonio Gutiérrez; Alicia Troncoso; César Hervás-Martínez (IEEE Trans. Cybern., 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)

Nearest neighbors with incremental learning for real-time forecasting of electricity demand. - Laura Melgar-García; David Gutiérrez-Avilés; Cristina Rubio-Escudero; Alicia Troncoso (ICDM (Workshops), 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)

Wrapper-based feature selection using regression trees to predict intrinsic viscosity of polymer. - R. Mortazavi; S. Mortazavi; Alicia Troncoso (Eng. Comput., 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)

A new hybrid method for predicting univariate and multivariate time series based on pattern forecasting. - Miguel Ángel Castán-Lascorz; P. Jiménez-Herrera; Alicia Troncoso Lora; Gualberto Asencio-Cortés (Inf. Sci., 2022)

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

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 (CISIS-ICEUTE, 2023)

Identification of Anomalies in Urban Sound Data with Autoencoders. - Laura Melgar-García; Maryam Hosseini; Alicia Troncoso (HAIS, 2023)

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

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)

Identifying novelties and anomalies for incremental learning in streaming time series forecasting. - Laura Melgar-García; David Gutiérrez-Avilés; Cristina Rubio-Escudero; Alicia Troncoso (Eng. Appl. Artif. Intell., 2023)

Streaming big time series forecasting based on nearest similar patterns with application to energy consumption. - P. Jiménez-Herrera; Laura Melgar-García; Gualberto Asencio-Cortés; Alicia Troncoso Lora (Log. J. IGPL, 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)

A novel distributed forecasting method based on information fusion and incremental learning for streaming time series. - Laura Melgar-García; David Gutiérrez-Avilés; Cristina Rubio-Escudero; 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)

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)

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)

Medium-term water consumption forecasting based on deep neural networks. - A. Gil-Gamboa; Pilar Paneque; Oscar Trull; Alicia Troncoso (Expert Syst. Appl., 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)

A novel incremental ensemble learning for real-time explainable forecasting of electricity price. - Laura Melgar-García; Alicia Troncoso (Knowl. Based Syst., 2024)

Bioinspired evolutionary metaheuristic based on COVID spread for discovering numerical association rules. - Cristina Herruzo-Lodeiro; Francesc Rodríguez-Díaz; Alicia Troncoso; María Martínez-Ballesteros (SAC, 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)

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 multimodal hybrid deep learning approach for pest forecasting using time series and satellite images. - Andrés Manuel Chacón-Maldonado; Gualberto Asencio-Cortés; Alicia Troncoso (Inf. Fusion, 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 novel method based on hybrid deep learning with explainability for olive fruit pest forecasting. - Andrés Manuel Chacón-Maldonado; Laura Melgar-García; Gualberto Asencio-Cortés; Alicia Troncoso (Neural Comput. 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)