José Luis Aznarte

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Jose M. BenitezFull Professor, Universidad de GranadaPreverjeni e-poštni naslov na decsai.ugr.es
Antonio Arauzo-AzofraUniversidad de CórdobaPreverjeni e-poštni naslov na uco.es
Rodrigo de Medrano LópezPhDPreverjeni e-poštni naslov na dia.uned.es
Francisco Martínez-ÁlvarezFull Professor, Data Science & Big Data Lab, Pablo de Olavide University of Seville, SpainPreverjeni e-poštni naslov na upo.es
Cristina Rubio-EscuderoSenior Lecturer, University of SevillaPreverjeni e-poštni naslov na us.es
Julio DíazResearch Professor at ISCIII.Director of the Reference Unit on Climate Change, Health andPreverjeni e-poštni naslov na isciii.es
Diego Nieto Lugilde (ORCID: 0000-00...Dpto. de Botánica, Ecología y Fisiología Vegetal. Universidad de Córdoba (https://ror.orgPreverjeni e-poštni naslov na uco.es
Francisca Alba SánchezProfessor of Botany, University of GranadaPreverjeni e-poštni naslov na ugr.es
C. De Linares FernandezProfesor Contratado Doctor (UGR)Preverjeni e-poštni naslov na ugr.es
Rafael Navajas-PérezAssociate Professor, Universidad de Granada, SpainPreverjeni e-poštni naslov na ugr.es
Marcelo C. MedeirosProfessor, Department of Economics, The University of Illinois at Urbana-ChampaignPreverjeni e-poštni naslov na illinois.edu
Georges KariniotakisFull Professor Mines Paris - PSL. Head of Renewable Energies & Smart Energy Systems Group (ERSEI)Preverjeni e-poštni naslov na minesparis.psl.eu
Espinar BellaMINES ParisTechPreverjeni e-poštni naslov na mines-paristech.fr
Robin GirardDirecteur de Recherche (Full Professor) at MINES Paris PSLPreverjeni e-poštni naslov na mines-paristech.fr
Christoph BergmeirUniversity of GranadaPreverjeni e-poštni naslov na monash.edu
Juan Luis CastroProfessor of Computer Science and Artificial Intelligence. University of GranadaPreverjeni e-poštni naslov na decsai.ugr.es

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José Luis Aznarte

Associate Professor. Artificial Intelligence Department, UNED.

Preverjeni e-poštni naslov na dia.uned.es - Domača stran

Artificial Intelligence Time series forecasting Deep learning


Naslov Razvrsti po navedbah Razvrsti po letniku Razvrsti po naslovu	Navedeno Navedeno	Leto
Shapley additive explanations for NO2 forecasting MV García, JL Aznarte Ecological Informatics 56, 101039, 2020	257	2020
Predicting air quality with deep learning LSTM: Towards comprehensive models R Navares, JL Aznarte Ecological Informatics 55, 101019, 2020	158	2020
Dynamic line rating using numerical weather predictions and machine learning: A case study JL Aznarte, N Siebert IEEE Transactions on Power Delivery 32 (1), 335-343, 2016	143	2016
Empirical study of feature selection methods based on individual feature evaluation for classification problems A Arauzo-Azofra, JL Aznarte, JM Benítez Expert systems with applications 38 (7), 8170-8177, 2011	137	2011
Forecasting airborne pollen concentration time series with neural and neuro-fuzzy models JL Aznarte, D Nieto-Lugilde, C de Linares Fernández, CD de la Guardia, ... Expert Systems with Applications 32 (4), 1218-1225, 2007	129	2007
Improving classification of pollen grain images of the POLEN23E dataset through three different applications of deep learning convolutional neural networks V Sevillano, JL Aznarte PloS one 13 (9), e0201807, 2018	107	2018
Precise automatic classification of 46 different pollen types with convolutional neural networks V Sevillano, K Holt, JL Aznarte Plos one 15 (6), e0229751, 2020	99	2020
Photovoltaic Forecasting: A state of the art B Espinar, JL Aznarte, R Girard, AM Moussa, G Kariniotakis 5th European PV-hybrid and mini-grid conference, Pages 250-255-ISBN 978-3 …, 2010	76	2010
Predictive performance of multi-model ensemble forecasts of COVID-19 across European nations K Sherratt, H Gruson, H Johnson, R Niehus, B Prasse, F Sandmann, ... Elife 12, e81916, 2023	69	2023
A spatio-temporal attention-based spot-forecasting framework for urban traffic prediction R de Medrano, JL Aznarte Applied Soft Computing 96, 106615, 2020	62	2020
Smooth transition autoregressive models and fuzzy rule-based systems: Functional equivalence and consequences JL Aznarte, JM Benítez, JL Castro Fuzzy sets and systems 158 (24), 2734-2745, 2007	44	2007
Financial time series forecasting with a bio-inspired fuzzy model JL Aznarte, J Alcalá-Fdez, A Arauzo-Azofra, JM Benítez Expert Systems with Applications 39 (16), 12302-12309, 2012	43	2012
Comparing ARIMA and computational intelligence methods to forecast daily hospital admissions due to circulatory and respiratory causes in Madrid R Navares, J Díaz, C Linares, JL Aznarte Stochastic environmental research and risk assessment 32, 2849-2859, 2018	41	2018
Earthquake magnitude prediction based on artificial neural networks: A survey E Florido, JL Aznarte, A Morales-Esteban, F Martínez-Álvarez Croatian Operational Research Review, 159-169, 2016	39	2016
Probabilistic forecasting for extreme NO2 pollution episodes JL Aznarte Environmental Pollution 229, 321-328, 2017	33	2017
Comparing quantile regression methods for probabilistic forecasting of NO₂ pollution levels SP Vasseur, JL Aznarte Scientific Reports 11 (1), 11592, 2021	31	2021
Deep learning classification of tooth scores made by different carnivores: achieving high accuracy when comparing African carnivore taxa and testing the hominin shift in the … N Abellán, B Jiménez-García, J Aznarte, E Baquedano, ... Archaeological and Anthropological Sciences 13 (2), 31, 2021	28	2021
Deep learning improves taphonomic resolution: high accuracy in differentiating tooth marks made by lions and jaguars B Jiménez-García, J Aznarte, N Abellán, E Baquedano, ... Journal of the Royal Society Interface 17 (168), 20200446, 2020	28	2020
Time series modeling and forecasting using memetic algorithms for regime-switching models C Bergmeir, I Triguero, D Molina, JL Aznarte, JM Benitez IEEE transactions on neural networks and learning systems 23 (11), 1841-1847, 2012	25	2012
A novel tree-based algorithm to discover seismic patterns in earthquake catalogs E Florido, G Asencio–Cortés, JL Aznarte, C Rubio-Escudero, ... Computers & Geosciences 115, 96-104, 2018	23	2018

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