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ORCIDJuan Jesús Ruiz-Aguilar
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2020 – today
- 2023
[j8]José Antonio Moscoso López, Javier González-Enrique
, Daniel Urda, Juan Jesús Ruiz-Aguilar, Ignacio J. Turias:
Hourly pollutants forecasting using a deep learning approach to obtain the AQI. Log. J. IGPL 31(4): 722-738 (2023)- [c15]María Gema Carrasco-García, María Inmaculada Rodríguez-García, Javier González-Enrique, Paloma Rocío Cubillas-Fernández, Juan Jesús Ruiz-Aguilar, Ignacio José Turias Domínguez:
Hyperspectral Technology for Oil Spills Detection by Using Artificial Neural Network Classifier. SOCO (1) 2023: 82-91 - 2022
- [c14]María Inmaculada Rodríguez-García, Javier González-Enrique, Juan Jesús Ruiz-Aguilar, Ignacio J. Turias:
A SO2 Pollution Concentrations Prediction Approach Using Autoencoders. SOCO 2022: 41-50 - [c13]Javier González-Enrique, Juan Jesús Ruiz-Aguilar, Eduardo Madrid Navarro, Rosa Martínez Álvarez-Castellanos, Ivan Felis Enguix, José M. Jerez, Ignacio J. Turias:
Deep Learning Approach for the Prediction of the Concentration of Chlorophyll ɑ in Seawater. A Case Study in El Mar Menor (Spain). SOCO 2022: 72-85 - 2021
- [j7]José Antonio Moscoso López, Daniel Urda, Juan Jesús Ruiz-Aguilar, Javier González-Enrique, Ignacio J. Turias:
A machine learning-based forecasting system of perishable cargo flow in maritime transport. Neurocomputing 452: 487-497 (2021) - [j6]Juan Jesús Ruiz-Aguilar, Ignacio Turias, Javier González-Enrique, Daniel Urda, David A. Elizondo:
A permutation entropy-based EMD-ANN forecasting ensemble approach for wind speed prediction. Neural Comput. Appl. 33(7): 2369-2391 (2021) - [j5]Daniel Urda, Francisco J. Veredas, Javier González-Enrique, Juan J. Ruiz-Aguilar, José M. Jerez, Ignacio J. Turias:
Deep neural networks architecture driven by problem-specific information. Neural Comput. Appl. 33(15): 9403-9423 (2021) - [j4]Javier González-Enrique, Juan Jesús Ruiz-Aguilar, José Antonio Moscoso López, Daniel Urda, Lipika Deka, Ignacio J. Turias:
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). Sensors 21(5): 1770 (2021) - 2020
- [j3]Juan Jesús Ruiz-Aguilar, Daniel Urda, José Antonio Moscoso López, Javier González-Enrique, Ignacio J. Turias:
A freight inspection volume forecasting approach using an aggregation/disaggregation procedure, machine learning and ensemble models. Neurocomputing 391: 282-291 (2020) - [c12]Juan Jesús Ruiz-Aguilar, Daniel Urda, José Antonio Moscoso López, Javier González-Enrique, Ignacio J. Turias:
Container Demand Forecasting at Border Posts of Ports: A Hybrid SARIMA-SOM-SVR Approach. OLA 2020: 69-81 - [c11]José Antonio Moscoso López, Daniel Urda, Javier González-Enrique, Juan Jesús Ruiz-Aguilar, Ignacio J. Turias:
Hourly Air Quality Index (AQI) Forecasting Using Machine Learning Methods. SOCO 2020: 123-132
2010 – 2019
- 2019
- [j2]José Antonio Moscoso López, Ignacio J. Turias, María Jesús Jiménez-Come, Juan Jesús Ruiz-Aguilar, María del Mar Cerbán:
A two-stage forecasting approach for short-term intermodal freight prediction. Int. Trans. Oper. Res. 26(2): 642-666 (2019) - [j1]Juan Jesús Ruiz-Aguilar, Ignacio J. Turias, José Antonio Moscoso López, María Jesús Jiménez-Come, María del Mar Cerbán:
Efficient goods inspection demand at ports: a comparative forecasting approach. Int. Trans. Oper. Res. 26(5): 1906-1934 (2019) - [c10]Héctor Mesa, Daniel Urda, Juan J. Ruiz-Aguilar, José Antonio Moscoso López, Juan Almagro, Patricia Acosta, Ignacio J. Turias:
A Machine Learning Approach to Determine Abundance of Inclusions in Stainless Steel. HAIS 2019: 504-513 - [c9]José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, Javier González-Enrique, Daniel Urda, Héctor Mesa, Ignacio J. Turias:
Ro-Ro Freight Prediction Using a Hybrid Approach Based on Empirical Mode Decomposition, Permutation Entropy and Artificial Neural Networks. HAIS 2019: 563-574 - [c8]Daniel Urda Muñoz, Juan Jesús Ruiz-Aguilar, Javier González-Enrique, Ignacio Turias Domínguez:
A Deep Ensemble Neural Network Approach to Improve Predictions of Container Inspection Volume. IWANN (1) 2019: 806-817 - [c7]José Antonio Moscoso López, Juan Jesús Ruiz-Aguilar, Daniel Urda, Javier González-Enrique, Ignacio José Turias:
Ro-Ro Freight Forecasting Based on an ANN-SVR Hybrid Approach. Case of the Strait of Gibraltar. IWANN (1) 2019: 818-831 - [c6]Javier González-Enrique, Juan Jesús Ruiz-Aguilar, José Antonio Moscoso López, Steffanie Van Roode, Daniel Urda, Ignacio J. Turias:
A Genetic Algorithm and Neural Network Stacking Ensemble Approach to Improve NO2 Level Estimations. IWANN (1) 2019: 856-867 - [c5]Steffanie Van Roode, Juan Jesús Ruiz-Aguilar, Francisco Javier Gonzalez-Enrique, Ignacio J. Turias:
A Hybrid Approach for Short-Term NO2 Forecasting: Case Study of Bay of Algeciras (Spain). SOCO 2019: 190-198 - 2018
- [c4]José Antonio Moscoso López, Ignacio J. Turias, Juan Jesús Ruiz-Aguilar, Francisco Javier Gonzalez-Enrique:
SVR-Ensemble Forecasting Approach for Ro-Ro Freight at Port of Algeciras (Spain). SOCO-CISIS-ICEUTE 2018: 357-366 - 2017
- [c3]Juan Jesús Ruiz-Aguilar, José Antonio Moscoso López, Ignacio J. Turias, Francisco Javier Gonzalez-Enrique:
Forecasting Freight Inspection Volume Using Bayesian Regularization Artificial Neural Networks: An Aggregation-Disaggregation Procedure. SOCO-CISIS-ICEUTE 2017: 179-187 - 2014
- [c2]José Antonio Moscoso López, Juan J. Ruiz-Aguilar, Ignacio J. Turias, María Mar Cerbán, María Jesús Jiménez-Come:
A Comparison of Forecasting Methods for Ro-Ro Traffic: A Case Study in the Strait of Gibraltar. DepCoS-RELCOMEX 2014: 345-353 - [c1]Juan J. Ruiz-Aguilar, Ignacio J. Turias, María Jesús Jiménez-Come, María Mar Cerbán:
Hybrid Approaches of Support Vector Regression and SARIMA Models to Forecast the Inspections Volume. HAIS 2014: 502-514
Coauthor Index
aka: Francisco Javier Gonzalez-Enrique
aka: Ignacio J. Turias
aka: Ignacio José Turias
aka: Ignacio Turias Domínguez
aka: Ignacio José Turias Domínguez
aka: Daniel Urda Muñoz
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