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: 2020 | 2019 | 2018 | 2016 | 2015 | 2013 | 2011 | 2010
Number of items: 15.

2020

Wang, Yihao and Huang, Yanli and Yang, Erfu (2020) Event-triggered communication for passivity and synchronisation of multi-weighted coupled neural networks with and without parameter uncertainties. IET Control Theory and Applications, 14 (9). pp. 1228-1239. ISSN 1751-8644

Dong, Ran and Mao, Xuerong and Birrell, Stewart A (2020) Exponential stabilisation of continuous-time periodic stochastic systems by feedback control based on periodic discrete-time observations. IET Control Theory and Applications, 14 (6). pp. 909-919. ISSN 1751-8644

Mei, Chunhui and Fei, Chen and Fei, Weiyin and Mao, Xuerong (2020) Stabilisation of highly non-linear continuous-time hybrid stochastic differential delay equations by discrete-time feedback control. IET Control Theory and Applications, 14 (2). pp. 313-323. ISSN 1751-8644

Xu, Huan and Ding, Feng and Yang, Erfu (2020) Recursive search-based identification algorithms for the exponential autoregressive time series model with coloured noise. IET Control Theory and Applications, 14 (2). pp. 262-270. ISSN 1751-8644

2019

Liu, Qinyao and Ding, Feng and Xu, Ling and Yang, Erfu (2019) Partially coupled gradient estimation algorithm for multivariable equation-error autoregressive moving average systems using the data filtering technique. IET Control Theory and Applications, 13 (5). pp. 642-650. ISSN 1751-8644

2018

Chen, Mengting and Ding, Feng and Yang, Erfu (2018) Gradient-based iterative parameter estimation for bilinear-in-parameter systems using the model decomposition technique. IET Control Theory and Applications, 12 (17). pp. 2380-2389. ISSN 1751-8644

Zhang, Xiao and Ding, Feng and Xu, Ling and Yang, Erfu (2018) State filtering-based least squares parameter estimation for bilinear systems using the hierarchical identification principle. IET Control Theory and Applications. pp. 1-10. ISSN 1751-8644

2016

Zhang, Jianhua and Zhou, Shuqing and Ren, Mifeng and Yue, Hong (2016) Adaptive neural network cascade control system with entropy-based design. IET Control Theory and Applications, 10 (10). pp. 1151-1160. ISSN 1751-8644

2015

Grimble, Michael and Majecki, Pawel (2015) Non-linear predictive generalised minimum variance state-dependent control. IET Control Theory and Applications. pp. 2438-2450. ISSN 1751-8644

Zhang, Liguo and Mao, Xuerong (2015) Vehicle density estimation of freeway traffic with unknown boundary demand-supply : an IMM approach. IET Control Theory and Applications, 9 (13). pp. 1989-1995. ISSN 1751-8644

2013

Grimble, Michael and Majeckie, Pawel (2013) Non-linear generalised minimum variance control using unstable state-dependent multivariable models. IET Control Theory and Applications. ISSN 1751-8644 (In Press)

2011

Hur, S.-H and Katebi, R. and Taylor, A. (2011) Model-based fault monitoring of a plastic film extrusion process. IET Control Theory and Applications, 5 (18). pp. 2075-2088. ISSN 1751-8644

Giovanini, L. (2011) Game approach to distributed model predictive control. IET Control Theory and Applications, 5 (15). pp. 1729-1739. ISSN 1751-8644

Wahab, N.A. and Katebi, M.R. and Balderud, J. and Rahmat, M.F. (2011) Data-driven adaptive model-based predictive control with application in wastewater systems. IET Control Theory and Applications, 5 (6). pp. 803-812. ISSN 1751-8644

2010

Grimble, M.J. and Majecki, P.M. (2010) Polynomial approach to nonlinear predictive generalized minimum variance control. IET Control Theory and Applications, 4 (3). pp. 411-424. ISSN 1751-8644

This list was generated on Mon Jul 6 04:23:34 2020 BST.