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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
Jump to: 2014 | 2012
Number of items: 5.

2014

Plumley, Charles Edward and Leithead, W.E. and Jamieson, P. and Graham, M. and Bossanyi, E.; (2014) Supplementing wind turbine pitch control with a trailing edge flap smart rotor. In: Renewable Power Generation Conference (RPG 2014), 3rd. IET, pp. 1-6. ISBN 978-1-84919-917-9

Plumley, Charles Edward and Leithead, Bill and Jamieson, Peter and Bossanyi, E. and Graham, Mike (2014) Comparison of individual pitch and smart rotor control strategies for load reduction. Journal of Physics: Conference Series, 524 (1). 012054. ISSN 1742-6588

Plumley, Charles Edward and Leithead, Bill and Jamieson, Peter and Graham, Mike and Bossanyi, E. (2014) Fault ride-through for a smart rotor DQ-axis controlled wind turbine with a jammed trailing edge flap. In: European Wind Energy Association 2014 Annual Conference, 2014-03-10 - 2014-03-13.

2012

Plumley, Charles Edward and Hill, David and McMillan, David and Bell, Keith and Infield, David; (2012) Validating wind field models for power system impact studies. In: International Conference on Sustainable Power Generation and Supply (SUPERGEN 2012). IEEE, CHN, pp. 1-6. ISBN 9781849196734

Plumley, Charles Edward and Wilson, Graeme and Kenyon, Andrew and Quail, Francis and Zitrou, Athena (2012) Diagnostics and prognostics utilising dynamic Bayesian networks applied to a wind turbine gearbox. In: International Conference on Condition Monitoringand Machine Failure Prevention Technologies, CM & MFPT 2012, 2012-06-12 - 2012-06-14.

This list was generated on Thu Aug 6 03:08:35 2020 BST.