M. J. Jiménez-Navarro

13 papers Misc 1Journal 7Unranked 5
YearRankTypeTitle / Venue / Authors
2026 J jnl
A novel interpretable ozone forecasting approach based on deep learning with masked residual connections.
Environ. Model. Softw.
Pablo Reina-Jiménez, M. J. Jiménez-Navarro, Gualberto Asencio-Cortés, Francisco Martínez-Álvarez, María Martínez-Ballesteros
2026 J jnl
Optimizing power and performance in time series forecasting: A feature selection approach for green computing.
Sustain. Comput. Informatics Syst.
Francisco Javier Galán-Sales, M. J. Jiménez-Navarro, Belén Vega-Márquez, José María Luna-Romera
2025 J jnl
Embedded feature selection for neural networks via learnable drop layer.
Log. J. IGPL
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Isabel Sofia Brito, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2024 J jnl
Explaining deep learning models for ozone pollution prediction via embedded feature selection.
Appl. Soft Comput.
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2024 J jnl
From simple to complex: a sequential method for enhancing time series forecasting with deep learning.
Log. J. IGPL
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Alicia Troncoso, Gualberto Asencio-Cortés
2024 — conf
Time Series Forecasting in Agriculture: Explainable Deep Learning with Lagged Feature Selection.
SOCO (1)
A. R. Troncoso-García, M. J. Jiménez-Navarro, Maria Lourdes Linares-Barrera, Isabel Sofia Brito, Francisco Martínez-Álvarez, María Martínez-Ballesteros
2023 — conf
Embedded Temporal Feature Selection for Time Series Forecasting Using Deep Learning.
IWANN (2)
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2023 — conf
Explaining Learned Patterns in Deep Learning by Association Rules Mining.
SOCO (2)
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2023 J jnl
PHILNet: A novel efficient approach for time series forecasting using deep learning.
Inf. Sci.
M. J. Jiménez-Navarro, María Martínez-Ballesteros, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2022 J jnl
DIAFAN-TL: An instance weighting-based transfer learning algorithm with application to phenology forecasting.
Knowl. Based Syst.
Miguel Angel Molina-Cabanillas, M. J. Jiménez-Navarro, Ricardo Arjona, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2021 Misc conf
A Model-Based Deep Transfer Learning Algorithm for Phenology Forecasting Using Satellite Imagery.
HAIS
M. Á. Molina, M. J. Jiménez-Navarro, Francisco Martínez-Álvarez, Gualberto Asencio-Cortés
2021 — conf
Electricity Consumption Time Series Forecasting Using Temporal Convolutional Networks.
CAEPIA
José F. Torres, M. J. Jiménez-Navarro, Francisco Martínez-Álvarez, Alicia Troncoso
2021 — conf
HLNet: A Novel Hierarchical Deep Neural Network for Time Series Forecasting.
SOCO
M. J. Jiménez-Navarro, Francisco Martínez-Álvarez, Alicia Troncoso, Gualberto Asencio-Cortés