Nonlinear Model Structure Identification Using Genetic Programming   [GP]

by

Gray, G., J., Murray-Smith, D., J., Li, Y. and Sharman, K., C.

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Info: Late Breaking Papers at the Genetic Programming 1996 Conference Stanford University July 28-31, 1996 (Conference proceedings), 1996, p. 32-37
Keywords:genetic algorithms, genetic programming
Abstract:
Genetic programming [GP] can be used to evolve an algebraic expression as part of an equation representing measured inputoutput response data. Parts of the nonlinear differential equations [DE] describing a dynamic system are identified along with their numerical parameters using genetic programming. [GP] 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.
Notes:
GP-96LB The email address for the bookstore for mail orders is mailorder@bookstore.stanford.edu Phone no 415-329-1217 or 800-533-2670 See also FACULTY OF ENGINEERING, GLASGOW G12 8QQ, U.K. TECHNICAL REPORT: CSC-96xxx
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BibTex:
@InProceedings{gray:1996:nmsti,
  author =       "Gary J. Gray and David J. Murray-Smith and Yun Li and
                 Ken C. Sharman",
  title =        "Nonlinear Model Structure Identification Using Genetic
                 Programming",
  booktitle =    "Late Breaking Papers at the Genetic Programming 1996
                 Conference Stanford University July 28-31, 1996",
  year =         "1996",
  editor =       "John R. Koza",
  pages =        "32--37",
  address =      "Stanford University, CA, USA",
  publisher_address = "Stanford University, Stanford, California
                 94305-3079, USA",
  month =        "28--31 " # jul,
  publisher =    "Stanford Bookstore",
  ISBN =         "0-18-201031-7",
  keywords =     "genetic algorithms, genetic programming",
  URL =          "http://www.mech.gla.ac.uk/~gary/tankgp96.ps",
  abstract =     "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.",
  notes =        "GP-96LB The email address for the bookstore for mail
                 orders is mailorder@bookstore.stanford.edu Phone no
                 415-329-1217 or 800-533-2670

                 See also FACULTY OF ENGINEERING, GLASGOW G12 8QQ, U.K.
                 TECHNICAL REPORT: CSC-96xxx",
}