• DocumentCode
    2021127
  • Title

    Evolutionary Neural Network Based on New Ant Colony Algorithm

  • Author

    Wei Gao

  • Author_Institution
    Wuhan Polytech. Univ., Wuhan
  • Volume
    1
  • fYear
    2008
  • fDate
    17-18 Oct. 2008
  • Firstpage
    318
  • Lastpage
    321
  • Abstract
    The evolutionary neural network is the combination of the evolutionary optimization algorithm and traditional neural network. To overcome the demerits of previously proposed evolutionary neural networks, combining the immune continuous ant colony algorithm proposed by author and BP neural network, a new evolutionary neural network whose architecture and connection weights evolve simultaneously is proposed. At last, through the typical XOR problem, the new evolutionary neural network is compared and analyzed with BP neural network, traditional evolutionary neural network based on genetic algorithm and evolutionary neural network based on evolutionary programming. The computing results show that the precision and efficiency of the new evolutionary neural network are all the best.
  • Keywords
    artificial immune systems; backpropagation; genetic algorithms; neural nets; BP neural network; artificial intelligence; evolutionary neural network; evolutionary programming; genetic algorithm; immune continuous ant colony algorithm; Algorithm design and analysis; Ant colony optimization; Evolutionary computation; Feedforward neural networks; Feeds; Flowcharts; Genetic algorithms; Genetic programming; Neural networks; Optimization methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Design, 2008. ISCID '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3311-7
  • Type

    conf

  • DOI
    10.1109/ISCID.2008.143
  • Filename
    4725617