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.

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Group by: Publication Date | Item type | No Grouping
Jump to: 2016 | 2015
Number of items: 3.

2016

Almaghairbe, Rafig and Roper, Marc; (2016) Automatically classifying test results by semi-supervised learning. In: 2016 IEEE 27th International Symposium on Software Reliability Engineering (ISSRE). IEEE, CAN, pp. 116-126. ISBN 978-1-4673-9003-3

Almaghairbe, Rafig and Roper, Marc (2016) Separating passing and failing test executions by clustering anomalies. Software Quality Journal. pp. 1-38. ISSN 1573-1367

2015

Almaghairbe, Rafig and Roper, Marc; (2015) Building test oracles by clustering failures. In: 2015 IEEE/ACM 10th International Workshop on Automation of Software Test (AST). IEEE, pp. 3-7.

This list was generated on Thu Jul 2 11:18:19 2020 BST.