M. J. Jiménez-Navarro
Orcid: 0000-0001-8514-4182Affiliations:
- University of Seville, Spain
According to our database1,
M. J. Jiménez-Navarro
authored at least 17 papers
between 2021 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Explaining deep learning models for ozone pollution prediction via embedded feature selection.
Appl. Soft Comput., 2024
Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, 2024
Proceedings of the Advances in Artificial Intelligence, 2024
Multi-Objective Lagged Feature Selection Based on Dependence Coefficient for Time-Series Forecasting.
Proceedings of the Advances in Artificial Intelligence, 2024
Toward Explaining Competitive Success in League of Legends: A Machine Learning Analysis.
Proceedings of the Advances in Artificial Intelligence, 2024
2023
A new deep learning architecture with inductive bias balance for transformer oil temperature forecasting.
J. Big Data, December, 2023
Inf. Sci., 2023
Proceedings of the 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023), 2023
Feature Selection Guided by CVOA Metaheuristic for Deep Neural Networks: Application to Multivariate Time Series Forecasting.
Proceedings of the 18th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2023), 2023
A bioinspired ensemble approach for multi-horizon reference evapotranspiration forecasting in Portugal.
Proceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023
Proceedings of the Advances in Computational Intelligence, 2023
Association Rule Analysis of Student Satisfaction Surveys for Teaching Quality Evaluation.
Proceedings of the International Joint Conference 16th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2023) 14th International Conference on EUropean Transnational Education (ICEUTE 2023), 2023
2022
DIAFAN-TL: An instance weighting-based transfer learning algorithm with application to phenology forecasting.
Knowl. Based Syst., 2022
Feature-Aware Drop Layer (FADL): A Nonparametric Neural Network Layer for Feature Selection.
Proceedings of the 17th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2022), 2022
2021
Proceedings of the 16th International Conference on Soft Computing Models in Industrial and Environmental Applications, 2021
A Model-Based Deep Transfer Learning Algorithm for Phenology Forecasting Using Satellite Imagery.
Proceedings of the Hybrid Artificial Intelligent Systems - 16th International Conference, 2021
Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks.
Proceedings of the Advances in Artificial Intelligence, 2021