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)

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)

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)

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)

Generating a seismogenic source zone model for the Pyrenees: A GIS-assisted triclustering approach. - José L. Amaro-Mellado; Laura Melgar-García; Cristina Rubio-Escudero; David Gutiérrez-Avilés (Comput. Geosci., 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)

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)

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)

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)

Feature Selection Guided by CVOA Metaheuristic for Deep Neural Networks: Application to Multivariate Time Series Forecasting. - Manuel Jesús Jiménez-Navarro; Camilo Restrepo Estrada; Laura Melgar-García; David Gutiérrez-Avilés (SOCO (1), 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 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)

Comparative Analysis of Deep Learning and Swarm-Optimized Random Forest for Groundwater Spring Potential Identification in Tropical Regions. - Viet-Ha Nhu; Pham Viet Hoa; Laura Melgar-García; Dieu Tien Bui (Remote. Sens., 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 novel incremental ensemble learning for real-time explainable forecasting of electricity price. - Laura Melgar-García; Alicia Troncoso (Knowl. Based Syst., 2024)

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)