Publicacions (43) Publicacions de María Del Mar Martínez Ballesteros

2025

  1. Nonlinear Ensemble Deep Learning Model for Energy Consumption Prediction with Bayesian Optimization

    Communications on Applied Nonlinear Analysis, Vol. 32, Núm. 1, pp. 155-172

2024

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

    AIMS Mathematics

  2. Evolutionary Feature Selection for Time-Series Forecasting

    Proceedings of the ACM Symposium on Applied Computing

  3. Explainable deep learning on multi-target time series forecasting: An air pollution use case

    Results in Engineering, Vol. 24

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

    Applied Soft Computing, Vol. 157

  5. Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting

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

  6. Uso de herramientas software colaborativas para el seguimiento, estudio y evaluación de clases de enseñanzas prácticas y desarrollo

    Enseñanza e innovación educativa en el ámbito universitario (Dykinson), pp. 1156-1167

2023

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

    Energies, Vol. 16, Núm. 5

  2. A Feature Selection and Association Rule Approach to Identify Genes Associated with Metastasis and Low Survival in Sarcoma

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

  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 approach based on association rules to add explainability to time series forecasting models

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

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

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

  7. A new treatment for sarcoma extracted from combination of miRNA deregulation and gene association rules

    Signal Transduction and Targeted Therapy

  8. Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation

    Lecture Notes in Networks and Systems

  9. 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)

  10. 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)

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

    Proceedings of the ACM Symposium on Applied Computing

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

    Lecture Notes in Networks and Systems

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

    Lecture Notes in Networks and Systems