Publicaciones (166) Publicaciones de Francisco Martínez Álvarez

2023

  1. A Bayesian Optimization-Based LSTM Model for Wind Power Forecasting in the Adama District, Ethiopia

    Energies, Vol. 16, Núm. 5

  2. A Cluster-Based Deep Learning Model for Energy Consumption Forecasting in Ethiopia

    Lecture Notes in Networks and Systems

  3. A New Hybrid CNN-LSTM for Wind Power Forecasting in Ethiopia

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

  4. A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal

    Proceedings of the ACM Symposium on Applied Computing

  5. A new Apache Spark-based framework for big data streaming forecasting in IoT networks

    Journal of Supercomputing, Vol. 79, Núm. 10, pp. 11078-11100

  6. A new approach based on association rules to add explainability to time series forecasting models

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

  7. A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting

    Journal of Big Data, Vol. 10, Núm. 1

  8. 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

    International Journal of Digital Earth, Vol. 16, Núm. 1, pp. 3661-3679

  9. Creating a homogenized earthquake catalog for Algeria and mapping the main seismic parameters using a geographic information system

    Journal of African Earth Sciences, Vol. 201

  10. Deep Learning-Based Approach for Sleep Apnea Detection Using Physiological Signals

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

  11. Electricity consumption forecasting with outliers handling based on clustering and deep learning with application to the Algerian market

    Expert Systems with Applications, Vol. 227

  12. Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning

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

  13. Evolutionary computation to explain deep learning models for time series forecasting

    Proceedings of the ACM Symposium on Applied Computing

  14. Explainable Artificial Intelligence for the Electric Vehicle Load Demand Forecasting Problem

    Lecture Notes in Networks and Systems

  15. Explainable hybrid deep learning and Coronavirus Optimization Algorithm for improving evapotranspiration forecasting

    Computers and Electronics in Agriculture, Vol. 215

  16. Explaining Learned Patterns in Deep Learning by Association Rules Mining

    Lecture Notes in Networks and Systems

  17. FS-Studio: An extensive and efficient feature selection experimentation tool for Weka Explorer

    SoftwareX, Vol. 23

  18. Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection

    Lecture Notes in Networks and Systems