Tham Ming Tan
TitleCited byYear
Advanced process control
MJ Willis, MT Tham
Department of Chemical and Process Engineering, University of Newcastle Upon …, 1994
12231994
Artificial neural networks in process engineering
MJ Willis, C Di Massimo, GA Montague, MT Tham, AJ Morris
IEE Proceedings D (Control Theory and Applications) 138 (3), 256-266, 1991
3041991
Artificial neural networks in process estimation and control
MJ Willis, GA Montague, C Di Massimo, MT Tham, AJ Morris
Automatica 28 (6), 1181-1187, 1992
2831992
Soft-sensors for process estimation and inferential control
MT Tham, GA Montague, AJ Morris, PA Lant
Journal of Process Control 1 (1), 3-14, 1991
1931991
A procedure for determining the topology of multilayer feedforward neural networks
Z Wang, C Di Massimo, MT Tham, AJ Morris
Neural Networks 7 (2), 291-300, 1994
1401994
Towards improved penicillin fermentation via artificial neural networks
C Di Massimo, GA Montague, MJ Willis, MT Tham, AJ Morris
Computers & chemical engineering 16 (4), 283-291, 1992
1341992
Non-linear principal components analysis using genetic programming
HG Hiden, MJ Willis, MT Tham, P Turner, GA Montague
IET Digital Library, 1997
1051997
Modelling chemical process systems using a multi-gene genetic programming algorithm
MP Hinchliffe, MJ Willis, H Hiden, MT Tham, B McKay, GW Barton
Genetic Programming: Proceedings of the First Annual Conference (late …, 1996
1001996
Enhancing bioprocess operability with generic software sensors
GA Montague, AJ Morris, MT Tham
Journal of Biotechnology 25 (1-2), 183-201, 1992
781992
Adaptive inferential control
MT Guilandoust, AJ Morris, MT Tham
IEE Proceedings D (Control Theory and Applications) 134 (3), 171-179, 1987
671987
Multivariable control: An introduction to decoupling control
MT Tham
Department of Chemical and Process Engineering, University of Newcastle Tyne, 1999
651999
Inverse model control using recurrent networks
C Kambhampati, RJ Craddock, M Tham, K Warwick
Mathematics and computers in simulation 51 (3-4), 181-199, 2000
512000
Multilayer neural networks: Approximated canonical decomposition of nonlinearity.
Z Wang
International Journal of Control 56, 655-672, 1992
471992
Soft-sensing: a solution to the problem of measurement delays
MT Tham, AJ Morris, G Montague
Chemical Engineering Research and Design 67 (6), 547-554, 1989
471989
Bioprocess model building using artificial neural networks
C Di Massimo, MJ Willis, GA Montague, MT Tham, AJ Morris
Bioprocess Engineering 7 (1-2), 77-82, 1991
461991
An adaptive estimation algorithm for inferential control
MT Guilandoust, AJ Morris, MT Tham
Industrial & engineering chemistry research 27 (9), 1658-1664, 1988
461988
Succeed at online validation and reconstruction of data
MT Tham, A Parr
Chemical engineering progress 90 (5), 46-56, 1994
431994
Bioprocess applications of model‐based estimation techniques
CD Massimo, PA Lant, A Saunders, GA Montague, MT Tham, AJ Morris
Journal of Chemical Technology & Biotechnology 53 (3), 265-277, 1992
421992
Multilayer feedforward neural networks: a canonical form approximation of nonlinearity
Z Wang, MT Tham, A JULIAN MORRIS
International Journal of Control 56 (3), 655-672, 1992
391992
Multivariable and multirate self-tuning control: a distillation column case study
MT Tham, F Vagi, AJ Morris, RK Wood
IEE Proceedings D (Control Theory and Applications) 138 (1), 9-24, 1991
381991
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