José Luis Aznarte

According to our database, José Luis Aznarte authored at least 29 papers between 2005 and 2021.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2021

On the inclusion of spatial information for spatio-temporal neural networks.

Rodrigo de Medrano, José Luis Aznarte

Neural Comput. Appl., 2021

SOCAIRE: Forecasting and monitoring urban air quality in Madrid.

Rodrigo de Medrano, Víctor de Buen Remiro, José Luis Aznarte

Environ. Model. Softw., 2021

A New Spatio-Temporal Neural Network Approach for Traffic Accident Forecasting.

Rodrigo de Medrano, José Luis Aznarte

Appl. Artif. Intell., 2021

2020

Forecasting hourly ${\hbox {NO}_{2}}$ concentrations by ensembling neural networks and mesoscale models.

Damir Valput, Ricardo Navares, José Luis Aznarte

Neural Comput. Appl., 2020

Deep learning architecture to predict daily hospital admissions.

Ricardo Navares, José Luis Aznarte

Neural Comput. Appl., 2020

Predicting air quality with deep learning LSTM: Towards comprehensive models.

Ricardo Navares, José Luis Aznarte

Ecol. Informatics, 2020

Shapley additive explanations for NO₂ forecasting.

María Vega García, José Luis Aznarte

Ecol. Informatics, 2020

A Spatio-Temporal Spot-Forecasting Framework forUrban Traffic Prediction.

Rodrigo de Medrano, José Luis Aznarte

CoRR, 2020

Probabilistic forecasting approaches for extreme NO₂ episodes: a comparison of models.

Sebastián Pérez Vasseur, José Luis Aznarte

CoRR, 2020

A spatio-temporal attention-based spot-forecasting framework for urban traffic prediction.

Rodrigo de Medrano, José Luis Aznarte

Appl. Soft Comput., 2020

2018

A novel tree-based algorithm to discover seismic patterns in earthquake catalogs.

Emilio Florido, Gualberto Asencio-Cortés, José Luis Aznarte, Cristina Rubio-Escudero, Francisco Martínez-Álvarez

Comput. Geosci., 2018

2015

Detecting precursory patterns to enhance earthquake prediction in Chile.

Emilio Florido, Francisco Martínez-Álvarez, Antonio Morales-Esteban, Jorge Reyes, José Luis Aznarte-Mellado

Comput. Geosci., 2015

2013

The Links between Statistical and Fuzzy Models for Time Series Analysis and Forecasting.

José Luis Aznarte, José Manuel Benítez

Proceedings of the Time Series Analysis, Modeling and Applications, 2013

2012

Time Series Modeling and Forecasting Using Memetic Algorithms for Regime-Switching Models.

Christoph Bergmeir, Isaac Triguero, Daniel Molina, José Luis Aznarte, José Manuel Benítez

IEEE Trans. Neural Networks Learn. Syst., 2012

Financial time series forecasting with a bio-inspired fuzzy model.

José Luis Aznarte, Jesús Alcalá-Fdez, Antonio Arauzo-Azofra, José Manuel Benítez

Expert Syst. Appl., 2012

2011

Empirical study of feature selection methods based on individual feature evaluation for classification problems.

Antonio Arauzo-Azofra, José Luis Aznarte, José Manuel Benítez

Expert Syst. Appl., 2011

A test for the homoscedasticity of the residuals in fuzzy rule-based forecasters.

José Luis Aznarte, Daniel Molina, Ana M. Sánchez, José Manuel Benítez

Appl. Intell., 2011

2010

Equivalences between neural-autoregressive time series models and fuzzy systems.

José Luis Aznarte, José Manuel Benítez

IEEE Trans. Neural Networks, 2010

Testing for Remaining Autocorrelation of the residuals in the Framework of Fuzzy Rule-Based Time Series Modelling.

José Luis Aznarte, Marcelo C. Medeiros, José Manuel Benítez

Int. J. Uncertain. Fuzziness Knowl. Based Syst., 2010

Linearity testing for fuzzy rule-based models.

José Luis Aznarte, Marcelo C. Medeiros, José Manuel Benítez

Fuzzy Sets Syst., 2010

Testing for Heteroskedasticity of the Residuals in Fuzzy Rule-Based Models.

José Luis Aznarte, José Manuel Benítez

Proceedings of the Trends in Applied Intelligent Systems, 2010

2009

Testing for Serial Independence of the Residuals in the Framework of Fuzzy Rule-Based Time Series Modeling.

José Luis Aznarte-Mellado, Antonio Arauzo, José Manuel Benítez Sánchez

Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

Empirical Study of Individual Feature Evaluators and Cutting Criteria for Feature Selection in Classification.

Antonio Arauzo-Azofra, José Luis Aznarte-Mellado, José Manuel Benítez

Proceedings of the Ninth International Conference on Intelligent Systems Design and Applications, 2009

2007

Smooth transition autoregressive models and fuzzy rule-based systems: Functional equivalence and consequences.

José Luis Aznarte, José Manuel Benítez, Juan Luis Castro

Fuzzy Sets Syst., 2007

Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models.

José Luis Aznarte, José Manuel Benítez Sánchez, Diego Nieto Lugilde, Concepción de Linares Fernández, Consuelo Díaz de la Guardia, Francisca Alba Sánchez

Expert Syst. Appl., 2007

SatDNA Analyzer: a computing tool for satellite-DNA evolutionary analysis.

Rafael Navajas-Pérez, Cristina Rubio-Escudero, José Luis Aznarte, Manuel Ruiz Rejón, Manuel A. Garrido-Ramos

Bioinform., 2007

satDNA Analyzer 1.2 as a Valuable Computing Tool for Evolutionary Analysis of Satellite-DNA Families: Revisiting Y-Linked Satellite-DNA Sequences of <i>Rumex </i> (Polygonaceae).

Rafael Navajas-Pérez, Manuel Ruiz Rejón, Manuel A. Garrido-Ramos, José Luis Aznarte, Cristina Rubio-Escudero

Proceedings of the Bioinformatics Research and Development, First International Conference, 2007

2006

On the Identifiability of TSK Additive Fuzzy Rule-Based Models.

José Luis Aznarte, José Manuel Benítez

Proceedings of the Soft Methods for Integrated Uncertainty Modelling, 2006

2005

Neuro-Fuzzy prediction of airborne pollen concentrations.

José Luis Aznarte, Diego Nieto Lugilde, José Manuel Benítez, Concepción de Linares Fernández

Proceedings of the Joint 4th Conference of the European Society for Fuzzy Logic and Technology and the 11th Rencontres Francophones sur la Logique Floue et ses Applications, 2005