Development of energy consumption model of abrasive machining process by a combined evolutionary computing approach

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@Article{Vijayaraghavan:2015:Measurement,
  author =       "R. Vijayaraghavan and A. Garg and 
                 V. Vijayaraghavan and Liang Gao",
  title =        "Development of energy consumption model of abrasive
                 machining process by a combined evolutionary computing
                 approach",
  journal =      "Measurement",
  volume =       "75",
  pages =        "171--179",
  year =         "2015",
  ISSN =         "0263-2241",
  DOI =          "doi:10.1016/j.measurement.2015.07.055",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0263224115004066",
  abstract =     "Abrasive machining is employed for improving surface
                 characteristics of components used in oil and gas
                 applications. Optimization of power consumed in
                 abrasive machining process is vital from environmental
                 standpoint that requires the formulation of the
                 generalized and an explicit mathematical model. In the
                 present work, we propose to study the power consumption
                 in abrasive machining process using a combined
                 evolutionary computing approach based on Multi-Adaptive
                 Regression Splines (MARS) and Genetic Programming (GP)
                 techniques. Sensitivity and parametric analysis have
                 also been conducted to capture the dynamics of process
                 by unveiling dominant input variables and hidden
                 non-linear relationships. It is concluded that
                 selection of optimal machining time and abrasive is
                 necessary for achieving better environmental
                 performance of abrasive machining process.",
  keywords =     "genetic algorithms, genetic programming, Abrasive
                 machining, MARS, Energy consumption, Modelling",
}

Genetic Programming entries for R Vijayaraghavan Akhil Garg Venkatesh Vijayaraghavan Liang Gao

Citations