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1 Ergebnisse
1
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/10498/24775
RT Journal T1 <Title>Artificial Neural Networks, Sequence-to-Sequence LSTMs, and Exogenous Variables as Analytical Tools for NO2 (Air Pollution) Forecasting: A Case Study in the Bay of Algeciras (Spain)</Title> UL https://suche.suub.uni-bremen.de/peid=base-ftunivcadiz:oai:rodin.uca.es:10498_24775&Exemplar=1&LAN=DE A1 González Enrique, Francisco Javier A1 Ruiz Aguilar, Juan Jesús A1 Moscoso López, José Antonio A1 Urda, Daniel A1 Deka, Lipika A1 Turias Domínguez, Ignacio José PB MDPI YR 2021 K1 forecasting K1 feature selection K1 air pollution K1 nitrogen dioxide K1 artificial neural networks K1 LSTMs K1 exogenous variables K1 deep learning K1 time series JF 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/ LK http://hdl.handle.net/10498/24775 DO http://hdl.handle.net/10498/24775 SF ELIB - SuUB Bremen
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