Picture of fish in sea

Open Access research that uses mathematical models to solve ecological problems...

Solving a variety of ecological and biological problems is the focus of marine population modelling research conducted within the Department of Mathematics & Statistics. Here research deploys mathematical models to better understanding issues relating to fish stock management, ecosystem dynamics, ocean currents, and the effects of multispecies interactions within diverse marine ecosystems.

Research work in marine population modelling interfaces with a number of other key research specialisms, including mathematical biology, epidemiology and statistical informatics, where investigations are improving human understanding of the behaviour of infectious diseases, particularly in relation to animal infections; but also the modelling of complex biological processes such as antibiotic prodcution in actinobacteria.

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

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Jump to: 2014 | 2013 | 2012
Number of items: 7.

2014

McMillan, David and Dinwoodie, Iain Allan and Wilson, Graeme and May, Allan and Hawker, Graeme (2014) Asset modelling challenges in the wind energy sector. In: CIGRE Session 2014, 2014-08-24 - 2014-08-30.

Wilson, G and McMillan, D (2014) Assessing wind farm reliability using weather dependent failure rates. Journal of Physics: Conference Series, 524 (1). 012181. ISSN 1742-6588

Wilson, Graeme and McMillan, David (2014) Quantifying the impact of wind speed on wind turbine component failure rates. In: European Wind Energy Association 2014 Annual Conference, 2014-03-10 - 2014-03-13.

2013

Wilson, Graeme and McMillan, David (2013) Modelling the impact of the environment on offshore wind turbine failure rates. In: EWEA Offshore 2013, 2013-11-19 - 2013-11-21.

Wilson, Graeme and McMillan, David (2013) Modeling the effects of seasonal weather and site conditions on wind turbine failure modes. In: ESREL 2013, 2013-09-30.

2012

Wilson, Graeme and McMillan, David (2012) Modeling the effects of the environment on wind turbine failure modes using neural networks. In: IET International Conference on Sustainable Power Generation and Supply, 2012-09-08 - 2012-09-09.

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 Mon Jul 13 23:39:38 2020 BST.