Grupo Nebrija de Investigación en Inteligencia Artificial y Sistemas Emergentes
ARIES
University of Strathclyde
Glasgow, Reino UnidoPublicaciones en colaboración con investigadores/as de University of Strathclyde (10)
2024
-
Analysis of attention mechanisms for the prediction of ship fuel oil consumption
Ingeniería naval, Núm. 1035, pp. 425-438
2023
-
Mar-RUL: A remaining useful life prediction approach for fault prognostics of marine machinery
Applied Ocean Research, Vol. 140
-
Recent advancements in data-driven methodologies for the fault diagnosis and prognosis of marine systems: A systematic review
Ocean Engineering, Vol. 284
2022
-
A novel framework for imputing large gaps of missing values from time series sensor data of marine machinery systems
Ships and Offshore Structures, Vol. 17, Núm. 8, pp. 1802-1811
-
A real-time data-driven framework for the identification of steady states of marine machinery
Applied Ocean Research, Vol. 121
-
Analysis of Time Series Imaging Approaches for the Application of Fault Classification of Marine Systems
Proceedings of the 32nd European Safety and Reliability Conference, ESREL 2022 - Understanding and Managing Risk and Reliability for a Sustainable Future
-
Analysis of Variational Autoencoders for Imputing Missing Values from Sensor Data of Marine Systems
Journal of Ship Research, Vol. 66, Núm. 3, pp. 193-202
-
Development of a time series imaging approach for fault classification of marine systems
Ocean Engineering, Vol. 263
-
RADIS: A real-time anomaly detection intelligent system for fault diagnosis of marine machinery
Expert Systems with Applications, Vol. 204
2020
-
Real-time data-driven missing data imputation for short-term sensor data of marine systems. A comparative study
Ocean Engineering, Vol. 218