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Nonlinear Model Structure Identification Using Genetic Programming

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Late Breaking Papers at the Genetic Programming 1996 Conference Stanford University July 28-31, 1996, Seite 32--37. Stanford University, CA, USA, Stanford Bookstore, (28--31 July 1996)

Zusammenfassung

Genetic programming can be used to evolve an algebraic expression as part of an equation representing measured inputoutput 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.

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