Improved Genetic Programming Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.4496

  author =       "Huifang Cheng and Yongqiang Zhang and Fangping Li",
  title =        "Improved Genetic Programming Algorithm",
  booktitle =    "International Asia Symposium on Intelligent
                 Interaction and Affective Computing, ASIA '09",
  year =         "2009",
  month =        dec,
  pages =        "168--171",
  abstract =     "The present study aims at improving the problem
                 solving ability of the canonical genetic programming
                 algorithm. The proposed method can be described as
                 follows. The first investigates initialising
                 population, the second investigates reproduction
                 operator, the third investigates crossover operator,
                 the fourth investigates mutation operation. This
                 approach is examined on two experiments about symbolic
                 regression. The results suggest that the new approach
                 is more effective and more efficient than the canonical
  keywords =     "genetic algorithms, genetic programming, canonical
                 genetic programming algorithm, crossover operator,
                 mutation operation, problem solving, reproduction
                 operator, symbolic regression, regression analysis",
  DOI =          "doi:10.1109/ASIA.2009.39",
  notes =        "Also known as \cite{5376006}",

Genetic Programming entries for Huifang Cheng Yongqiang Zhang Fangping Li