Zobrazeno 1 - 10
of 23
pro vyhledávání: '"José Antonio Moscoso-López"'
Autor:
Javier González-Enrique, Juan Jesús Ruiz-Aguilar, José Antonio Moscoso-López, Daniel Urda, Lipika Deka, Ignacio J. Turias
Publikováno v:
Sensors, Vol 21, Iss 5, p 1770 (2021)
This study aims to produce accurate predictions of the NO2 concentrations at a specific station of a monitoring network located in the Bay of Algeciras (Spain). Artificial neural networks (ANNs) and sequence-to-sequence long short-term memory network
Externí odkaz:
https://doaj.org/article/308bf6ac2d86432287ff9b542a328b19
Autor:
Juan Jesús Ruiz-Aguilar, José Antonio Moscoso-López, Daniel Urda, Javier González-Enrique, Ignacio Turias
Publikováno v:
Applied Sciences, Vol 10, Iss 23, p 8326 (2020)
An accurate prediction of freight volume at the sanitary facilities of seaports is a key factor to improve planning operations and resource allocation. This study proposes a hybrid approach to forecast container volume at the sanitary facilities of a
Externí odkaz:
https://doaj.org/article/a4f695a4d6384360bc6ba2a5572ecacb
Autor:
Javier González-Enrique, Daniel Urda, Juan Jesús Ruiz-Aguilar, Ignacio J. Turias, José Antonio Moscoso-López
Publikováno v:
Neurocomputing. 452:487-497
The uncertainty cargo flow problem establishes a limitation in ports management where decision-making processes need accurate information of the future values. This work aims at predicting the future values of Ro-Ro perishable cargo flow at the Port
Autor:
Ignacio J. Turias, Daniel Urda, José Antonio Moscoso-López, Javier González-Enrique, Juan Jesús Ruiz-Aguilar
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 35:1999-2019
This study presents a comparison between sixteen filter ranking methods applied to a real air pollution problem. Adaptations of the Minimum-Redundancy-Maximum-Relevance (mRMR) algorithm to use the Spearman's rank correlation, the kernel canonical cor
Publikováno v:
Transportation Research Procedia. 58:363-369
Autor:
Juan Jesús Ruiz-Aguilar, José Antonio Moscoso-López, Daniel Urda, Ignacio J. Turias, Javier González-Enrique
Publikováno v:
Neurocomputing. 391:282-291
Machine learning methods are a powerful tool to detect workload peaks and congestion in goods inspection facilities of seaports. In this paper, a time series data of freight inspection volume at the Border Inspections Posts in the Port of Algeciras B
Autor:
José Antonio Moscoso-López, Javier González-Enrique, Daniel Urda, Juan Jesús Ruiz-Aguilar, Ignacio J Turias
Publikováno v:
Logic Journal of the IGPL.
The Air Quality Index (AQI) shows the state of air pollution in a unique and more understandable way. This work aims to forecast the AQI in Algeciras (Spain) 8 hours in advance. The AQI is calculated indirectly through the predicted concentrations of
Autor:
Juan Jesús Ruiz-Aguilar, Ignacio J. Turias, José Antonio Moscoso-López, Leonardo Franco, Javier González-Enrique
Publikováno v:
Stochastic Environmental Research and Risk Assessment. 33:801-815
This study focuses on how to determine the most relevant variables in order to estimate the hourly NO2 concentrations in a monitoring network located in the Bay of Algeciras (Spain). For each station of the network, artificial neural networks and mul
Autor:
Javier González-Enrique, Daniel Urda, Ignacio J. Turias, José Antonio Moscoso-López, Juan Jesús Ruiz-Aguilar
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030578015
SOCO
SOCO
Air Quality Index (AQI) is an index to inform the daily air quality. AQI is a dimensionless quantity to show the state of air pollution simplifying the information of concentrations in \(\mu g/m^3\). Air quality indexes have been established for each
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::312530586be22a26a8dc423b8d468e81
https://doi.org/10.1007/978-3-030-57802-2_12
https://doi.org/10.1007/978-3-030-57802-2_12
Autor:
Daniel Urda, Javier González-Enrique, Ignacio J. Turias, Juan Jesús Ruiz-Aguilar, José Antonio Moscoso-López
Publikováno v:
Communications in Computer and Information Science ISBN: 9783030419127
OLA
OLA
An accurate forecast of freight demand at sanitary facilities of ports is one of the key challeng-es for transport policymakers to better allocate resources and to improve planning operations. This paper proposes a combined hybrid approach to predict
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9957866cf653e421ff2bccabe9eb1bf5
https://doi.org/10.1007/978-3-030-41913-4_7
https://doi.org/10.1007/978-3-030-41913-4_7