Mark Willis
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GPTIPS: an open source genetic programming toolbox for multigene symbolic regression
DP Searson, DE Leahy, MJ Willis
Proceedings of the International multiconference of engineers and computer …, 2010
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
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
Steady-state modelling of chemical process systems using genetic programming
B McKay, M Willis, G Barton
Computers & chemical engineering 21 (9), 981-996, 1997
Artificial Neural Networks-Studies in-Process Modeling and Control
AJ Morris, GA Montague, MJ Willis
Chemical engineering research & design 72 (1), 3-19, 1994
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
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
Non-linear principal components analysis using genetic programming
HG Hiden, MJ Willis, MT Tham, GA Montague
Computers & Chemical Engineering 23 (3), 413-425, 1999
Proportional-integral-derivative control
MJ Willis
Dept. of Chemical and Process Engineering University of Newcastle, 1999
Using a tree structured genetic algorithm to perform symbolic regression
B McKay, MJ Willis, GW Barton
First international conference on genetic algorithms in engineering systems …, 1995
Genetic programming: An introduction and survey of applications
MJ Willis, HG Hiden, P Marenbach, B McKay, GA Montague
Second international conference on genetic algorithms in engineering systems …, 1997
Co‐evolution of non‐linear PLS model components
D Searson, M Willis, G Montague
Journal of Chemometrics: A Journal of the Chemometrics Society 21 (12), 592-603, 2007
Systems modelling using genetic programming
M Willis, H Hiden, M Hinchliffe, B McKay, GW Barton
Computers & chemical engineering 21, S1161-S1166, 1997
Advanced process control
MJ Willis, MT Tham
Department of Chemical and Process Engineering, University of Newcastle Upon …, 1994
Dynamic systems modelling using genetic programming
MP Hinchliffe, MJ Willis
Computers & Chemical Engineering 27 (12), 1841-1854, 2003
Bioprocess model building using artificial neural networks
C Di Massimo, MJ Willis, GA Montague, MT Tham, AJ Morris
Bioprocess Engineering 7 (1), 77-82, 1991
Hybrid approach to modeling an industrial polyethylene process
M Hinchliffe, G Montague, M Willis, A Burke
AIChE journal 49 (12), 3127-3137, 2003
Product identification and distribution from the oscillatory versus non-oscillatory palladium (II) iodide-catalysed oxidative carbonylation of phenylacetylene
C Grosjean, K Novakovic, SK Scott, A Whiting, MJ Willis, AR Wright
Journal of Molecular Catalysis A: Chemical 284 (1-2), 33-39, 2008
Achieving pH and Qr oscillations in a palladium-catalysed phenylacetylene oxidative carbonylation reaction using an automated reactor system
K Novakovic, C Grosjean, SK Scott, A Whiting, MJ Willis, AR Wright
Chemical physics letters 435 (1-3), 142-147, 2007
Modeling and control of a food extrusion process
J Elsey, J Riepenhausen, B McKay, GW Barton, M Willis
Computers & chemical engineering 21, S361-S366, 1997
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