A novel genetic programming approach to nonlinear system modelling: application to the DAMADICS benchmark problem

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@Article{Metenidis:2004:EAAI,
  author =       "Mihai Florin Metenidis and Marcin Witczak and 
                 Jozef Korbicz",
  title =        "A novel genetic programming approach to nonlinear
                 system modelling: application to the {DAMADICS}
                 benchmark problem",
  journal =      "Engineering Applications of Artificial Intelligence",
  year =         "2004",
  volume =       "17",
  pages =        "363--370",
  number =       "4",
  abstract =     "Nonlinear system modelling is a diverse research area
                 where different kinds of methodologies can be employed.
                 However, due to the large variety of this field, no
                 approach imposes itself as the best one. The difficulty
                 of system modelling consists in the necessity of
                 approximating both the structure and the parameters of
                 a system. That is why the choice of the approach to be
                 used usually depends on a specific application. This
                 paper presents a modified genetic programming approach
                 for model structure selection combined with a classical
                 technique for parameter estimation. In particular,
                 various combinations of parameterised fixed length
                 trees are proposed as candidate model structures. The
                 algorithms that can be used to obtain a suitable form
                 of these structures are proposed as well. The final
                 part of the paper justifies the possibility of using
                 this approach in practice, i.e. a comprehensive
                 empirical study is performed with the data acquired
                 from an industrial actuator.",
  owner =        "wlangdon",
  URL =          "http://www.sciencedirect.com/science/article/B6V2M-4CKFH3B-1/2/49d6ac641b4455bbc65260281aa1ee55",
  keywords =     "genetic algorithms, genetic programming, system
                 modelling, Parameter estimation",
  doi =          "doi:10.1016/j.engappai.2004.04.009",
}

Genetic Programming entries for Mihai Florin Metenidis Marcin Witczak Jozef Korbicz