Drafting Force Forecasting Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@Article{nibikora2011,

• 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=10.1.1.1002.5139",
• 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

Citations