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José Luis Aznarte
Person information
- affiliation: Universidad Nacional de Educacion a Distancia (UNED), Department of Artificial Intelligence, Madrid, Spain
- affiliation (PhD 2008): University of Granada, Spain
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2020 – today
- 2021
- [j20]Rodrigo de Medrano
, José Luis Aznarte
A New Spatio-Temporal Neural Network Approach for Traffic Accident Forecasting. Appl. Artif. Intell. 35(10): 782-801 (2021) - [j19]Rodrigo de Medrano
SOCAIRE: Forecasting and monitoring urban air quality in Madrid. Environ. Model. Softw. 143: 105084 (2021) - [j18]Rodrigo de Medrano
On the inclusion of spatial information for spatio-temporal neural networks. Neural Comput. Appl. 33(21): 14723-14740 (2021) - 2020
- [j17]Rodrigo de Medrano
A spatio-temporal attention-based spot-forecasting framework for urban traffic prediction. Appl. Soft Comput. 96: 106615 (2020) - [j16]Ricardo Navares, José Luis Aznarte
Predicting air quality with deep learning LSTM: Towards comprehensive models. Ecol. Informatics 55 (2020) - [j15]María Vega García, José Luis Aznarte
Shapley additive explanations for NO2 forecasting. Ecol. Informatics 56: 101039 (2020) - [j14]Damir Valput, Ricardo Navares, José Luis Aznarte
Forecasting hourly ${\hbox {NO}_{2}}$ concentrations by ensembling neural networks and mesoscale models. Neural Comput. Appl. 32(13): 9331-9342 (2020) - [j13]Ricardo Navares, José Luis Aznarte
Deep learning architecture to predict daily hospital admissions. Neural Comput. Appl. 32(20): 16235-16244 (2020) - [i4]Sebastián Pérez Vasseur, José Luis Aznarte:
Probabilistic forecasting approaches for extreme NO2 episodes: a comparison of models. CoRR abs/2003.11356 (2020) - [i3]Rodrigo de Medrano, José Luis Aznarte:
A Spatio-Temporal Spot-Forecasting Framework forUrban Traffic Prediction. CoRR abs/2003.13977 (2020) - [i2]Rodrigo de Medrano, José Luis Aznarte:
On the Inclusion of Spatial Information for Spatio-Temporal Neural Networks. CoRR abs/2007.07559 (2020) - [i1]Rodrigo de Medrano, Víctor de Buen Remiro, José Luis Aznarte:
SOCAIRE: Forecasting and Monitoring Urban Air Quality in Madrid. CoRR abs/2011.09741 (2020)
2010 – 2019
- 2018
- [j12]Emilio Florido, Gualberto Asencio-Cortés
A novel tree-based algorithm to discover seismic patterns in earthquake catalogs. Comput. Geosci. 115: 96-104 (2018) - 2015
- [j11]Emilio Florido, Francisco Martínez-Álvarez
Detecting precursory patterns to enhance earthquake prediction in Chile. Comput. Geosci. 76: 112-120 (2015) - 2013
- [p1]José Luis Aznarte
The Links between Statistical and Fuzzy Models for Time Series Analysis and Forecasting. Time Series Analysis, Modeling and Applications 2013: 1-30 - 2012
- [j10]José Luis Aznarte
Financial time series forecasting with a bio-inspired fuzzy model. Expert Syst. Appl. 39(16): 12302-12309 (2012) - [j9]Christoph Bergmeir
Time Series Modeling and Forecasting Using Memetic Algorithms for Regime-Switching Models. IEEE Trans. Neural Networks Learn. Syst. 23(11): 1841-1847 (2012) - 2011
- [j8]José Luis Aznarte
A test for the homoscedasticity of the residuals in fuzzy rule-based forecasters. Appl. Intell. 34(3): 386-393 (2011) - [j7]Antonio Arauzo-Azofra
Empirical study of feature selection methods based on individual feature evaluation for classification problems. Expert Syst. Appl. 38(7): 8170-8177 (2011) - 2010
- [j6]José Luis Aznarte
Linearity testing for fuzzy rule-based models. Fuzzy Sets Syst. 161(13): 1836-1851 (2010) - [j5]José Luis Aznarte
Testing for Remaining Autocorrelation of the residuals in the Framework of Fuzzy Rule-Based Time Series Modelling. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 18(4): 371-387 (2010) - [j4]José Luis Aznarte
Equivalences between neural-autoregressive time series models and fuzzy systems. IEEE Trans. Neural Networks 21(9): 1434-1444 (2010) - [c6]José Luis Aznarte
Testing for Heteroskedasticity of the Residuals in Fuzzy Rule-Based Models. IEA/AIE (2) 2010: 239-246
2000 – 2009
- 2009
- [c5]Antonio Arauzo-Azofra
Empirical Study of Individual Feature Evaluators and Cutting Criteria for Feature Selection in Classification. ISDA 2009: 541-546 - [c4]José Luis Aznarte-Mellado
Testing for Serial Independence of the Residuals in the Framework of Fuzzy Rule-Based Time Series Modeling. ISDA 2009: 1383-1387 - 2007
- [j3]Rafael Navajas-Pérez
SatDNA Analyzer: a computing tool for satellite-DNA evolutionary analysis. Bioinform. 23(6): 767-768 (2007) - [j2]José Luis Aznarte
Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models. Expert Syst. Appl. 32(4): 1218-1225 (2007) - [j1]José Luis Aznarte
Smooth transition autoregressive models and fuzzy rule-based systems: Functional equivalence and consequences. Fuzzy Sets Syst. 158(24): 2734-2745 (2007) - [c3]Rafael Navajas-Pérez, Manuel Ruiz Rejón, Manuel A. Garrido-Ramos, José Luis Aznarte, Cristina Rubio-Escudero:
satDNA Analyzer 1.2 as a Valuable Computing Tool for Evolutionary Analysis of Satellite-DNA Families: Revisiting Y-Linked Satellite-DNA Sequences of Rumex (Polygonaceae). BIRD 2007: 131-139 - 2006
- [c2]José Luis Aznarte
On the Identifiability of TSK Additive Fuzzy Rule-Based Models. SMPS 2006: 79-86 - 2005
- [c1]José Luis Aznarte, Diego Nieto Lugilde, José Manuel Benítez, Concepción de Linares Fernández:
Neuro-Fuzzy prediction of airborne pollen concentrations. EUSFLAT Conf. 2005: 1325-1330
Coauthor Index
aka: José Manuel Benítez Sánchez
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