A Novel Approximation Algorithm Based on Genetic Programming in Digital Learning Environment

Created by W.Langdon from gp-bibliography.bib Revision:1.4208

  author =       "Yaqin Li and Cao Yuan and Cong Zhang and Shigao Li and 
                 Kaiqiong Sun and Xuan Wang",
  booktitle =    "2015 International Conference of Educational
                 Innovation through Technology (EITT)",
  title =        "A Novel Approximation Algorithm Based on Genetic
                 Programming in Digital Learning Environment",
  year =         "2015",
  pages =        "33--36",
  abstract =     "With the development of information and the
                 integration of media, it has great practical
                 significance and research value to build a digital
                 learning environment based on the complicated
                 electronic circuit. However, the complicated electronic
                 circuit in real-time need a complex and expensive
                 technology. In order to overcome the high cost and
                 technology, an approach was proposed for simplifying
                 generation by approximating the excitations with
                 rectangular pulses, triangular pulses and cosine waves
                 which can be implemented with a moderate cost in
                 analogical electronics. In this work, we improved a
                 novel approach based on genetic programming, The
                 differences between theoretical excitation signals and
                 the approximation driving pulses, related to their
                 excitation effects, were minimised by genetic
                 programming. From these results, the accuracy of
                 simulation can be improved by the new approach, the
                 difference between theoretical complicated digital
                 signals and the new approach is reduced. A trade off is
                 obtained between the costs of implementation of digital
                 processing in digital learning environments.",
  keywords =     "genetic algorithms, genetic programming, Biological
                 cells, Electronic circuits, Encoding, Evolutionary
                 computation, Optimisation, approximation algorithm,
                 digital learning environment",
  DOI =          "doi:10.1109/EITT.2015.13",
  month =        oct,
  notes =        "Also known as \cite{7446142}",

Genetic Programming entries for Yaqin Li Cao Yuan Cong Zhang Shigao Li Kaiqiong Sun Xuan Wang