Publications by the researcher in collaboration with María Del Mar Martínez Ballesteros (31)

2025

  1. A new metric based on association rules to assess feature-attribution explainability techniques for time series forecasting

    IEEE Transactions on Pattern Analysis and Machine Intelligence

  2. A novel approach based on clustering and optimized ensemble deep learning for energy consumption forecasting in Ethiopia

    Neurocomputing, Vol. 637

2024

  1. Advances in time series forecasting: innovative methods and applications

    AIMS Mathematics

  2. Explainable Deep Learning with Embedded Feature Selection for Electricity Demand Forecasting

    Proceedings of International Conference on Smart Systems and Technologies, SST 2024

  3. Explaining deep learning models for ozone pollution prediction via embedded feature selection

    Applied Soft Computing, Vol. 157

  4. From simple to complex: A sequential method for enhancing time series forecasting with deep learning

    Logic Journal of the IGPL, Vol. 32, Núm. 6, pp. 986-1003

  5. Time Series Forecasting in Agriculture: Explainable Deep Learning with Lagged Feature Selection

    Lecture Notes in Networks and Systems

2023

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

    Energies, Vol. 16, Núm. 5

  2. 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)

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

    Proceedings of the ACM Symposium on Applied Computing

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

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

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

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

  6. 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)

  7. 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)

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

    Proceedings of the ACM Symposium on Applied Computing

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

    Lecture Notes in Networks and Systems

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

    Lecture Notes in Networks and Systems

  11. PHILNet: A novel efficient approach for time series forecasting using deep learning

    Information Sciences, Vol. 632, pp. 815-832

2022

  1. A novel approach to discover numerical association based on the coronavirus optimization algorithm

    Proceedings of the ACM Symposium on Applied Computing

  2. Explainable machine learning for sleep apnea prediction

    Procedia Computer Science