Drafting Force Forecasting Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4448

  author =       "Ildephonse Nibikora and Jun Wang3",
  title =        "Drafting Force Forecasting Using Genetic Programming",
  journal =      "Advanced Materials Research",
  year =         "2011",
  month =        "2",
  volume =       "175",
  pages =        "355--359",
  keywords =     "genetic algorithms, genetic programming, drafting
                 force, drawing frame, drafting process parameters",
  ISSN =         "1662-8985",
  publisher =    "Trans Tech Publications",
  URL =          "http://citeseerx.ist.psu.edu/viewdoc/summary?doi=",
  URL =          "http://www.scientific.net/AMR.175-176.355.pdf",
  DOI =          "doi:10.4028/www.scientific.net/AMR.175-176.355",
  size =         "5 pages",
  abstract =     "Genetic programming was used to find out a
                 mathematical model for drafting force from drafting
                 process parameters on the drawing frame, which fits the
                 experimental data as much as possible. The study used
                 rayon fibers as the raw material in the mini-draw
                 frame. The process parameters on the draw frame such as
                 front roller speed, front roller draft, back roller
                 speed and back roller draft as variables were
                 investigated. The paper used the principle that there
                 is linear relationship between drafting force and
                 deformation from the strain gauges in the sensor. The
                 data obtained from online measurement device was used
                 for training and testing on the genetic programming. A
                 comparison between experimental and predicted data was
                 done. The results show very good agreement between the
                 experimental and predicted values. Furthermore, this
                 article shows that genetic programming can provide
                 further use for setting up the machine process
                 parameters without requiring an expert in the field.",

Genetic Programming entries for Ildephonse Nibikora Jun Wang3