• DocumentCode
    3678544
  • Title

    An Improved Parallel Algorithm of Genetic Programming Based on the Framework of MapReduce

  • Author

    Zhang Song;Ma Jun;Zhao Yang-Yang;Liu Qiong

  • Author_Institution
    BeiJing NUMBERONE Technol. Dev. Co., Ltd., Beijing, China
  • fYear
    2015
  • Firstpage
    221
  • Lastpage
    225
  • Abstract
    Genetic programming lacks convergence prematurely and operating efficiency. This paper is to study this problem that integrates the genetic programming theory with the framework of Map/Reduce. This is to improve the efficiency by parallel and distributed capability proved by Map/Reduce. Our experiments show that the improved parallel algorithm of genetic programming under the framework of Map/Reduce has the better performance than the conventional approaches.
  • Keywords
    "Genetic programming","Sociology","Statistics","Algorithm design and analysis","Computers","Convergence","Classification algorithms"
  • Publisher
    ieee
  • Conference_Titel
    Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2015 International Conference on
  • Type

    conf

  • DOI
    10.1109/CyberC.2015.37
  • Filename
    7307816
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3678544