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Open Access research that better understands changing marine ecologies...

Strathprints makes available scholarly Open Access content by researchers in the Department of Mathematics & Statistics.

Mathematics & Statistics hosts the Marine Population Modelling group which is engaged in research into topics surrounding marine resource modelling and ecology. Recent work has included important developments in the population modelling of marine species.

Explore the Open Access research of Mathematics & Statistics. Or explore all of Strathclyde's Open Access research...

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Number of items: 9.

Velasco-Gallego, Christian and Lazakis, Iraklis (2022) Development of a time series imaging approach for fault classification of marine systems. Ocean Engineering, 263. 112297. ISSN 0029-8018

Velasco-Gallego, Christian and Lazakis, Iraklis (2022) RADIS : a real-time anomaly detection intelligent system for fault diagnosis of marine machinery. Expert Systems with Applications, 204. 117634. ISSN 0957-4174

Velasco-Gallego, Christian and Lazakis, Iraklis (2022) Analysis of variational autoencoders for imputing missing values from sensor data of marine systems. Journal of Ship Research, 66 (3). 193–203. ISSN 0022-4502

Velasco, Christian and Lazakis, Iraklis; Leva, Maria Chiara and Patelli, Edoardo and Podofillini, Luca and Wilson, Simon, eds. (2022) Analysis of time series imaging approaches for the application of fault classification of marine systems. In: Proceedings of the 32nd European Safety and Reliability Conference. Research Publishing, IRL. ISBN 9819730000000

Velasco-Gallego, Christian and Lazakis, Iraklis (2022) A novel framework for imputing large gaps of missing values from time series sensor data of marine machinery systems. Ships and Offshore Structures, 17 (8). pp. 1802-1811. ISSN 1754-212X

Velasco-Gallego, Christian and Lazakis, Iraklis (2022) A real-time data-driven framework for the identification of steady states of marine machinery. Applied Ocean Research, 121. 103052. ISSN 0141-1187

Velasco-Gallego, Christian and Lazakis, Iraklis (2021) A real-time semi-supervised anomaly detection framework for fault diagnosis of marine machinery systems. In: SNAME WES Paper Contest 2021, 2021-06-10 - 2021-06-11, London.

Velasco-Gallego, C and Lazakis, I; (2021) Data imputation of missing values from marine systems sensor data. Evaluation, visualisation, and sensor failure detection. In: RINA Maritime Innovation and Emerging Technologies Online Conference 2021 Proceedings. Royal Institution of Naval Architects, London.

Velasco, Christian and Lazakis, Iraklis (2020) Real-time data-driven missing data imputation for short-term sensor data of marine systems. A comparative study. Ocean Engineering, 218. 108261. ISSN 0029-8018

This list was generated on Tue Apr 23 11:12:55 2024 BST.