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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Number of items: 5.

2015

Zhang, Jinfang and Yue, Hong and Zhou, Jinglin (2015) Predictive PDF control in shaping of molecular weight distribution based-on a new modelling Algorithm. Journal of Process Control, 30. pp. 80-89. ISSN 0959-1524

2009

Vaccarini, M. and Longhi, S. and Katebi, M.R. (2009) Unconstrained networked decentralized model predictive control. Journal of Process Control, 19 (2). pp. 328-339. ISSN 0959-1524

2006

Xia, H. and Majecki, P.M. and Ordys, A.W. and Grimble, M.J. (2006) Performance assessment of MIMO systems based on I/O delay information. Journal of Process Control, 16 (4). pp. 373-383. ISSN 0959-1524

2004

Grimble, M.J. (2004) Integral minimum variance control and benchmarking. Journal of Process Control, 14 (2). pp. 177-191. ISSN 0959-1524

2003

Imsland, L. and Findeisen, R. and Bullinger, E. and Allgöwer, F. and Foss, B.A. (2003) A note on stability, robustness and performance of output feedback nonlinear model predictive control. Journal of Process Control, 13 (7). pp. 633-644. ISSN 0959-1524

This list was generated on Sun Jul 5 16:15:19 2020 BST.