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Nonlinear model structure identification using genetic programming

Gray, G.J., Murray-Smith, D.J., Li, Y., and Sharman, K.C. (1996) Nonlinear model structure identification using genetic programming. In: Genetic Programming '96 Conference (GP '96), 28-31 Jul 1996, Stanford, CA.

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Abstract

Genetic programming can be used to eveolve an algebraic expression as part of an equation representing measured input-output response data. Parts of the nonlinear differential equations describing a dynamic system are identified along with their numerical parameters using genetic programming. The results of several such optimisations are analysed to produce a nonlinear physical representation of the dynamic system. This method is applied to the identification of fluid flow through pipes in a coupled water tank system. A representative nonlinear model is identified.

Item Type:Conference Proceedings
Additional Information:Published in: Koza, J.R. (ed.) Late Breaking Papers at the Genetic Programming 1996 Conference. Stanford: Stanford University Press, 1996. ISBN: 9780182010318.
Keywords:Genetic programming, dynamic model, nonlinear, optimisation, system identification, fluid flow.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Murray-Smith, Prof David and Li, Prof Yun
Authors: Gray, G.J., Murray-Smith, D.J., Li, Y., and Sharman, K.C.
Subjects:Q Science > QA Mathematics > QA76 Computer software
T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
College of Science and Engineering > School of Engineering

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