Genetic Programming Based on an Adaptive Regularization Method

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Wu:2006:iccis,
  author =       "Yanling Wu and Jiangang Lu and Youxian Sun",
  title =        "Genetic Programming Based on an Adaptive
                 Regularization Method",
  booktitle =    "International Conference on Computational Intelligence
                 and Security, 2006",
  year =         "2006",
  volume =       "1",
  pages =        "324--327",
  address =      "Guangzhou",
  month =        nov,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "1-4244-0605-6",
  DOI =          "doi:10.1109/ICCIAS.2006.294148",
  abstract =     "A proper model of a bioprocess is very important for
                 the development of industrial bioprocesses. Here,
                 genetic programming (GP) and genetic algorithm (GA) are
                 used to model the Avermectin fermentation process. To
                 get more accuracy model without losing generalisation,
                 a regularisation term is integrated into the fitness
                 function and an adaptive method to optimise
                 regularisation parameter is proposed to balance
                 training accuracy and the curvature of a nonlinear
                 model. Furthermore, a new protected approach is
                 proposed and experiments show that with the method, the
                 amount the undesired sharp changes in the predicting
                 value decreases largely",
  notes =        "National Lab. of Ind. Control Technol., Zhejiang
                 Univ., Hangzhou",
}

Genetic Programming entries for Yanling Wu Jiangang Lu Youxian Sun

Citations