Nonlinear identification of aircraft gas-turbine dynamics

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "A. E. Ruano and P. J. Fleming and C. Teixeira and 
                 K. Rodriguez-Vazquez and C. M. Fonseca",
  title =        "Nonlinear identification of aircraft gas-turbine
  journal =      "Neurocomputing",
  year =         "2003",
  volume =       "55",
  pages =        "551--579",
  number =       "3-4",
  keywords =     "genetic algorithms, genetic programming, Gas-turbine
                 engines, Nonlinear system identification, Neural
                 networks, Multiobjective optimisation",
  ISSN =         "0925-2312",
  owner =        "wlangdon",
  URL =          "",
  DOI =          "doi:10.1016/S0925-2312(03)00393-X",
  abstract =     "Identification results for the shaft-speed dynamics of
                 an aircraft gas turbine, under normal operation, are
                 presented. As it has been found that the dynamics vary
                 with the operating point, nonlinear models are
                 employed. Two different approaches are considered: NARX
                 models, and neural network models, namely multilayer
                 perceptrons, radial basis function networks and
                 B-spline networks. A special attention is given to
                 genetic programming, in a multiobjective fashion, to
                 determine the structure of NARMAX and B-spline

Genetic Programming entries for Antonio E Ruano Peter J Fleming C Teixeira Katya Rodriguez-Vazquez Carlos M Fonseca