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Powering innovation in artificial intelligence with Open Access research...

Artificial intelligence (AI) and machine learning (ML) together represent a research frontier with a wide variety of discipline specific applications. At Strathclyde researchers in Computer & Information Sciences are exploring improved AI planning models to enable improved decision making by automous agents. Meanwhile, research conducted by the Aerospace Centre of Excellence is using AI and computational techniques to optimize the efficacy of certain astronautic applications. This includes 'global trajectory optimization' to aircraft and spacecraft design, from the planning and scheduling for autonomous vehicles to the synthesis of robust controllers for airplanes or satellites.

AI is also transforming the research agenda within Finance, where researchers are exploring the potential of AI and machine learning in evaluating banking risks and in new, emerging aspects of FinTech.

Explore some of this Open Access research from Computer & Information Sciences, Aerospace Centre of Excellence and Finance. Or explore all of Strathclyde's Open Access research...

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Group by: Publication Date | Item type | No Grouping
Number of items: 11.

Article

Raptodimos, Yiannis and Lazakis, Iraklis (2020) Application of NARX neural network for predicting marine engine performance parameters. Ships and Offshore Structures, 15 (4). pp. 443-452. ISSN 1754-212X

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

Book Section

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, GBR.

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, GBR.

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, GBR, pp. 95-101.

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

Raptodimos, Yiannis and Lazakis, Iraklis and Theotokatos, Gerasimos and Salinas, Raul and Moreno, Alfonso; Jin, HyunWoo and Tang, Huang and Akselsen, Odd M. and Lee, Yongwon, eds. (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, GRC, 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: International Conference on Smart Ship Technology 2016. Royal Institution of Naval Architects, GBR. ISBN 9781909024502

Conference or Workshop Item

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, 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 Sat Aug 8 13:30:45 2020 BST.