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Open Access research at the forefront of modern physics

Strathprints makes available scholarly Open Access content by researchers in the Department of Physics, based within the Faculty of Science.

Hosting the Institute of Photonics and with specialisms in plasmas, optics, and nanoscience, the research conducted at the Department of Physics is considered world leading and, based on the REF2014 GPA scores, is considered by Times Higher Education to be first in the UK. One particular specialism is atoms, beams and plasmas where topics within free electron physics, accelerator science, plasma physics and atomic and molecular spectroscopy are explored.

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Group by: Publication Date | Item type | No Grouping
Jump to: 2019 | 2018 | 2017 | 2016 | 2015
Number of items: 11.

2019

Raptodimos, Yiannis and Lazakis, Iraklis (2019) Application of NARX neural network for predicting marine engine performance parameters. Ships and Offshore Structures. ISSN 1754-212X (In Press)

2018

Lazakis, I. and Raptodimos, Y. and Varelas, T. (2018) Predicting ship machinery system condition through analytical reliability tools and artificial neural networks. Ocean Engineering, 152. pp. 404-415. ISSN 0029-8018

Raptodimos, Yiannis and Lazakis, Iraklis (2018) Using artificial neural network-self-organising map for data clustering of marine engine condition monitoring applications. Ships and Offshore Structures, 13 (6). pp. 649-656. ISSN 1754-212X

Raptodimos, Yiannis and Lazakis, Iraklis (2018) Implementing unsupervised learning algorithm for marine engine data clustering applications. In: Proceedings of the 2018 Smart Ship Technology Conference. Royal Institution of Naval Architects, London.

2017

Raptodimos, Y and Lazakis, I (2017) Fault tree analysis and artificial neural network modelling for establishing a predictive ship machinery maintenance methodology. In: International Conference on Smart Ship Technology 2017. Royal Institution of Naval Architects, London.

2016

Raptodimos, Yiannis and Lazakis, Iraklis (2016) An artificial neural network approach for predicting the performance of ship machinery equipment. In: Maritime Safety and Operations 2016 Conference Proceedings. University of Strathclyde Publishing, pp. 95-101.

Dikis, K. and Lazakis, I. and Michala, A. L. and Raptodimos, Y. and Theotokatos, G. (2016) Dynamic risk and reliability assessment for ship machinery decision making. In: Risk, Reliability and Safety. CRC/Taylor & Francis Group, London, pp. 685-692. ISBN 9781315374987

Raptodimos, Yiannis and Lazakis, Iraklis and Theotokatos, Gerasimos and Salinas, Raul and Moreno, Alfonso (2016) Collection and analysis of data for ship condition monitoring aiming at enhanced reliability and safety. In: Proceedings of The Twenty-sixth (2016) International Ocean and Engineering Conference. Proceedings of the Annual International Offshore and Polar Engineering Conference, 4 . International Society of Offshore and Polar Engineers (ISOPE), Cupertino, California, pp. 828-835. ISBN 9781880653883

Raptodimos, Yiannis and Lazakis, Iraklis and Theotokatos, Gerasimos and Varelas, Takis and Drikos, Leonidas (2016) Ship sensors data collection and analysis for condition monitoring of ship structures and machinery systems. In: Smart Ship Technology, 2016-01-26 - 2016-01-27, The Royal Institution of Naval Architects.

Raptodimos, Yiannis and Lazakis, Iraklis and Theotokatos, Gerasimos and Varelas, Takis and Drikos, Leonidas (2016) Ship sensors data collection and analysis for condition monitoring of ship structures and machinery systems. In: International Conference on Smart Ship Technology 2016. Royal Institution of Naval Architects, London. ISBN 9781909024502

2015

Raptodimos, Y. and Lazakis, I. and Varelas, T. and Papadakis, A. and Drikos, L. (2015) Defining ship structural and machinery onboard measurement campaign for energy efficient operations. In: International Conference on Shipping in Changing Climates, 2015-11-24 - 2015-11-26, Technology & Innovation Centre.

This list was generated on Tue Aug 20 15:04:42 2019 BST.