Integrated genetic programming and genetic algorithm approach to predict surface roughness

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@Article{Brezocnik:2003:MMP,
  author =       "Miran Brezocnik and Miha Kovacic",
  title =        "Integrated genetic programming and genetic algorithm
                 approach to predict surface roughness",
  journal =      "Materials and Manufacturing Processes",
  year =         "2003",
  volume =       "18",
  number =       "3",
  pages =        "475--491",
  month =        may,
  keywords =     "genetic algorithms, genetic programming, Manufacturing
                 systems, Surface roughness, Milling",
  DOI =          "doi:10.1081/AMP-120022023",
  abstract =     "we propose a new integrated genetic programming and
                 genetic algorithm approach to predict surface roughness
                 in end-milling. Four independent variables, spindle
                 speed, feed rate, depth of cut, and vibrations, were
                 measured. Those variables influence the dependent
                 variable (i.e., surface roughness). On the basis of
                 training data set, different models for surface
                 roughness were developed by genetic programming. The
                 floating-point constants of the best model were
                 additionally optimised by a genetic algorithm. Accuracy
                 of the model was proved on the testing data set. By
                 using the proposed approach, more accurate prediction
                 of surface roughness was reached than if only modelling
                 by genetic programming had been carried out. It was
                 also established that the surface roughness is most
                 influenced by the feed rate, whereas the vibrations
                 increase the prediction accuracy.",
}

Genetic Programming entries for Miran Brezocnik Miha Kovacic

Citations