E-LIB Suche - Ergebnisse für: Moscoso Lopez, Jose Antonio

1

Prediction of container filling for the selective waste col..:

Rodríguez López, Juana Carmen ; Rodríguez-García, M. Inmaculada ; Moscoso Lopez, Jose Antonio...
Transportation Research Procedia. 58 (2021) - p. 583-590 , 2021

Link: https://doi.org/10.1016/..

2

Towards the numerical ground-borne vibrations predictive mo..:

Moreno, Andrés García ; Ruiz Aguilar, Juan Jesús ; Moscoso López, José Antonio
Transportation Research Procedia. 58 (2021) - p. 363-369 , 2021

Link: https://doi.org/10.1016/..

3

Air pollution relevance analysis in the bay of Algeciras (S..:

Rodríguez García, María Inmaculada ; González Enrique, Francisco Javier ; Moscoso López, José Antonio..
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098160-B-I00/ES/DEEP LEARNING IN AIR POLLUTION FORECASTING/. , 2023

Link: http://hdl.handle.net/10..

4

Hourly pollutants forecasting using a deep learning approac..:

Moscoso-López, José Antonio ; González-Enrique, Javier ; Urda, Daniel..
Logic Journal of the IGPL. 31 (2022) 4 - p. 722-738 , 2022

Link: https://doi.org/10.1093/..

5

Comparison of maritime transport influence of SO2 levels in..:

Rodríguez García, María Inmaculada ; González Enrique, Francisco Javier ; Moscoso López, José Antonio...
2352-1457. , 2022

Link: http://hdl.handle.net/10..

6

Prediction of container filling for the selective waste col..:

Rodríguez López, Juana Carmen ; Rodríguez García, María Inmaculada ; Moscoso López, José Antonio...
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098160-B-I00/ES/DEEP LEARNING IN AIR POLLUTION FORECASTING/. , 2022

Link: http://hdl.handle.net/10..

7

Towards the numerical ground-borne vibrations predictive mo..:

García Moreno, Andrés ; Ruiz Águilar, Juan Jesús ; Moscoso López, José Antonio
2352-1457. , 2022

Link: http://hdl.handle.net/10..

8

A machine learning-based forecasting system of perishable c..:

Moscoso-López, José Antonio ; Urda, Daniel ; Ruiz-Aguilar, Juan Jesús..
Neurocomputing. 452 (2021) - p. 487-497 , 2021

Link: https://doi.org/10.1016/..

9

Artificial Neural Networks, Sequence-to-Sequence LSTMs, and..:

González-Enrique, Javier ; Ruiz-Aguilar, Juan Jesús ; Moscoso-López, José Antonio...
Sensors. 21 (2021) 5 - p. 1770 , 2021

Link: https://doi.org/10.3390/..

10

A comparison of ranking filter methods applied to the estim..:

González-Enrique, Javier ; Ruiz-Aguilar, Juan Jesús ; Moscoso-López, José Antonio..
Stochastic Environmental Research and Risk Assessment. 35 (2021) 10 - p. 1999-2019 , 2021

Link: https://doi.org/10.1007/..

11

A Clustering-Based Hybrid Support Vector Regression Model t..:

Ruiz Aguilar, Juan Jesús ; Moscoso López, José Antonio ; Urda, Daniel..
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098160-B-I00/ES/DEEP LEARNING IN AIR POLLUTION FORECASTING/. , 2021

Link: http://hdl.handle.net/10..

12

Towards the numerical ground-borne vibrations predictive mo..:

García Moreno, Andrés ; Ruiz Aguilar, Juan Jesús ; Moscoso López, José Antonio
R-Evolucionando el transporte. , 2021

Link: http://hdl.handle.net/10..

13

Comparison of maritime transport influence of SO2 levels in..:

Rodríguez García, Inmaculada ; Moscoso López, José Antonio ; Ruiz Aguilar, Juan Jesús...
R-Evolucionando el transporte. , 2021

Link: http://hdl.handle.net/10..

14

Artificial Neural Networks, Sequence-to-Sequence LSTMs, and..:

González Enrique, Francisco Javier ; Ruiz Aguilar, Juan Jesús ; Moscoso López, José Antonio...
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-098160-B-I00/ES/DEEP LEARNING IN AIR POLLUTION FORECASTING/. , 2021

Link: http://hdl.handle.net/10..

15

Artificial Neural Networks, Sequence-to-Sequence LSTMs, and..:

González Enrique, Francisco Javier ; Ruiz Aguilar, Juan Jesús ; Moscoso López, José Antonio...
Sensors. 2021, V. 21, n. 5, 1770. , 2021

Link: http://hdl.handle.net/10..