Publicaciones en colaboración con investigadores/as de Universidad de Sevilla (12)

2023

  1. A novel distributed forecasting method based on information fusion and incremental learning for streaming time series

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

  2. Explainable Artificial Intelligence for Education: A Real Case of a University Subject Switched to Python

    Lecture Notes in Networks and Systems

  3. Feature Selection Guided by CVOA Metaheuristic for Deep Neural Networks: Application to Multivariate Time Series Forecasting

    Lecture Notes in Networks and Systems

  4. Identifying novelties and anomalies for incremental learning in streaming time series forecasting

    Engineering Applications of Artificial Intelligence, Vol. 123

2022

  1. A new big data triclustering approach for extracting three-dimensional patterns in precision agriculture

    Neurocomputing, Vol. 500, pp. 268-278

  2. Nearest neighbors with incremental learning for real-time forecasting of electricity demand

    IEEE International Conference on Data Mining Workshops, ICDMW

2021

  1. Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering

    Advances in Intelligent Systems and Computing

  2. Discovering Spatio-Temporal Patterns in Precision Agriculture Based on Triclustering

    15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020): Burgos, Spain ; September 2020

  3. Discovering three-dimensional patterns in real-time from data streams: An online triclustering approach

    Information Sciences, Vol. 558, pp. 174-193

  4. Generating a seismogenic source zone model for the Pyrenees: A GIS-assisted triclustering approach

    Computers and Geosciences, Vol. 150

  5. Nearest Neighbors-Based Forecasting for Electricity Demand Time Series in Streaming

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

2020

  1. Coronavirus Optimization Algorithm: A Bioinspired Metaheuristic Based on the COVID-19 Propagation Model

    Big data, Vol. 8, Núm. 4, pp. 308-322