Publications (188) Francisco Martínez Álvarez publications

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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, Vol. 47, Núm. 5, pp. 4140-4155

  2. 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, Vol. 47, Núm. 5, pp. 4140-4155

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

    Neurocomputing, Vol. 637

  4. A novel explainable AI framework for medical image classification integrating statistical, visual, and rule-based methods

    Medical Image Analysis, Vol. 105

  5. A partitioning incremental algorithm using adaptive Mahalanobis fuzzy clustering and identifying the most appropriate partition

    Pattern Analysis and Applications, Vol. 28, Núm. 1

  6. Energy-efficient transfer learning for water consumption forecasting

    Sustainable Computing: Informatics and Systems, Vol. 46

  7. Forecasting basal area increment in forest ecosystems using deep learning: A multi-species analysis in the Himalayas

    Ecological Informatics, Vol. 85

  8. MetaGen: A framework for metaheuristic development and hyperparameter optimization in machine and deep learning

    Neurocomputing, Vol. 637

  9. Preface

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

  10. Preface

    Lecture Notes in Networks and Systems

  11. Preface

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

2024

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

    AIMS Mathematics

  2. An Experimental Comparison of Qiskit and Pennylane for Hybrid Quantum-Classical Support Vector Machines

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

  3. An evolutionary triclustering approach to discover electricity consumption patterns in France

    Proceedings of the ACM Symposium on Applied Computing

  4. Emerging trends in big data analytics and natural disasters

    Computers and Geosciences

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

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

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

    Applied Soft Computing, Vol. 157

  7. 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

  8. Ground-Level Ozone Forecasting Using Explainable Machine Learning

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

  9. Pattern sequence-based algorithm for multivariate big data time series forecasting: Application to electricity consumption

    Future Generation Computer Systems, Vol. 154, pp. 397-412