César Peláez-Rodriguez

1. FISTER, Dušan, PÉREZ-ARACIL, Jorge, PELÁEZ-RODRIGUEZ, César, DEL SER, Javier, SALCEDO-SANZ, Sancho. Accurate long-term air temperature prediction with a fusion of artificial intelligence and data reduction techniques. In: ArXiv.org. Ithaca (NY): Cornell University Library. 2023, 33 str. DOI: 10.48550/arXiv.2209.15424. [COBISS.SI-ID 142262787]

2. PELÁEZ-RODRIGUEZ, César, PÉREZ-ARACIL, Jorge, FISTER, Dušan, PRIETO- GODINO, Luis, DEO, Ravinesh, SALCEDO-SANZ, Sancho. A hierarchical classification/regression algorithm for improving extreme wind speed events prediction. Renewable energy. Dec. 2022, vol. 201, str. 157-178, ilustr. ISSN 1879-0682. DOI: 10.1016/j.renene.2022.11.042. [COBISS.SI-ID 142267651]

3. FISTER, Dušan, PÉREZ-ARACIL, Jorge, PELÁEZ-RODRIGUEZ, César, DEL SER, Javier, SALCEDO-SANZ, Sancho. Accurate long-term air temperature prediction with Machine Learning models and data reduction techniques. Applied soft computing. [Print ed.]. Mar. 2023, vol. 136, [article no.] 110118, 18 str. ISSN 1568-4946. DOI: 10.1016/j.asoc.2023.110118. [COBISS.SI-ID 142272259]
project: 101003876-CLINT CLIMATE INTELLIGENCE Extreme events detection, attribution and adaptation design using machine learning (CLINT); funder: European Union, through H2020
project: PID2020-115454GB-C21; funder: Spanish Ministry of Science and Innovation (MICINN)

4. PELÁEZ-RODRIGUEZ, César, PÉREZ-ARACIL, Jorge, DE LOPEZ-DIZ, Alba, CASANOVA-MATEO, Carlos, FISTER, Dušan, JIMÉNEZ-FERNÁNDEZ, Silvia, SALCEDO-SANZ, Sancho. Deep learning ensembles for accurate fog-related low-visibility events forecasting. Neurocomputing. [Onilne ed.]. 7 Sep. 2023, vol. 547, 26 str., ilustr. ISSN 1872-8286. DOI: 10.1016/j.neucom.2023.126435. [COBISS.SI-ID 156841219]
project: This research has been partially supported by the project PID2020-115454 GB-C21 of the Spanish Ministry of Science and Innovation (MICINN)

5. FISTER, Dušan, PÉREZ-ARACIL, Jorge, PELÁEZ-RODRIGUEZ, César, DROUARD, Marie, ZANINELLI, Pablo G., BARRIOPEDRO-CEPERO, David, GARCIA HERRERA, Ricardo, SALCEDO-SANZ, Sancho. Towards the effective autoencoder architecture to detect weather anomalies. In: EGU General Assembly 2023 : Vienna, Austria & Online : 23–28 April 2023. [S. l.]: European Geosciences Union, 2023. 1 spletni vir. DOI: 10.5194/egusphere-egu23-7457. [COBISS.SI-ID 156847363]

6. FISTER, Dušan, PELÁEZ-RODRIGUEZ, César, CORNEJO-BUENO, L., PÉREZ-ARACIL, Jorge, SALCEDO-SANZ, Sancho. Autoencoder framework for general forecasting. In: FERRÁNDEZ VICENTE, José Manuel (ed.), VAL CALVO, Mikel (ed.), ADELI, Hojjat (ed.). Bioinspired systems for translational applications : from robotics to social engineering : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024 Olhâo, Portugal, June 4–7, 2024 : proceedings, part II. Cham: Springer, cop. 2024. Str. 314-322, ilustr. Lecture notes in computer science (Internet), 14675. ISBN 978-3-031-61137-7, ISBN 978-3-031-61136-0. ISSN 1611-3349. DOI: 10.1007/978-3-031-61137-7_29. [COBISS.SI-ID 204788995]

7. PELÁEZ-RODRIGUEZ, César, PÉREZ-ARACIL, Jorge, FISTER, Dušan, TORRES- LÓPEZ, Ricardo, SALCEDO-SANZ, Sancho. Bike sharing and cable car demand forecasting using machine learning and deep learning multivariate time series approaches. Expert systems with applications. [Online ed.]. 15 March 2024, [article no.] 122264, vol. 238, part e, 22 str., ilustr. ISSN 1873-6793. Digitalna knjižnica Univerze v Mariboru – DKUM, DOI: 10.1016/j.eswa.2023.122264. [COBISS.SI-ID 190816515]
project: This research has been supported partially by the project PID2020- 115454GB-C21 of the Spanish Ministry of Science and Innovation (MICINN). The authors acknowledge the financial support from the Slovenian Research and Innovation Agency (ARIS) (Research Core Funding No. P2-0057 & P2-0042).

8. PÉREZ-ARACIL, Jorge, FISTER, Dušan, MARINA, C. M., PELÁEZ-RODRIGUEZ, César, CORNEJO-BUENO, L., GUTIÉRREZ, P. A., GIULIANI, Matteo, CASTELLETI, A., SALCEDO-SANZ, Sancho. Long-term temperature prediction with hybrid autoencoder algorithms. Expert systems with applications. [Online ed.]. Sep. 2024, vol. 23, [article no.] 100185, 13 str., ilustr. ISSN 1873-6793. Digitalna knjižnica Univerze v Mariboru – DKUM, DOI: 10.1016/j.acags.2024.100185. [COBISS.SI-ID 204807683]
project: This research has been partially supported by the European Union, through H2020 Project ‘‘CLIMATE INTELLIGENCE Extreme events detection, attribution and adaptation design using machine learning (CLINT)’’, Ref: 101003876-CLINT. This research has also been partially supported by the project PID2020-115454GB-C21 of the Spanish Ministry of Science and Innovation (MICINN). The present study has been supported by the European Commission, project Test and Experiment Facilities for the Agri-Food Domain, AgriFoodTEF (grant ref.: DIGITAL-2022-CLOUD-AI-02, 101100622). This research is part of the ENIA International Chair in Agriculture, University of Córdoba (TSI100921-2023-3), funded by the Secretary of State for Digitalisation and Artificial Intelligence and by the European Union- Next Generation EU. Recovery, Transformation and Resilience Plan.

9. PELÁEZ-RODRIGUEZ, César, CORNEJO-BUENO, L., FISTER, Dušan, PÉREZ-ARACIL, Jorge, SALCEDO-SANZ, Sancho. Prediction of extreme wave heights via a fuzzy-based cascade ensemble model. In: FERRÁNDEZ VICENTE, José Manuel (ed.), VAL CALVO, Mikel (ed.), ADELI, Hojjat (ed.). Bioinspired systems for translational applications : from robotics to social engineering : 10th International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2024 Olhâo, Portugal, June 4–7, 2024 : proceedings, part II. Cham: Springer, cop. 2024. Str. 323-332, ilustr. Lecture notes in computer science (Internet), 14675. ISBN 978-3-031-61137-7, ISBN 978-3-031-61136-0. ISSN 1611-3349. [COBISS.SI-ID 204799491]
project: This research has been partially supported by the project PID2020-115454GB-C21 of the Spanish Ministry of Science and Innovation (MICINN).