• DocumentCode
    2452246
  • Title

    Chromosome Recognition as An Effective Algorithm using Polynomial Functional Neural Networks

  • Author

    Tan, Xuping ; Liu, Jiancheng

  • Author_Institution
    Math. Dept., Guangdong Agric.-Ind.-Bus. Polytech. Coll., Guangzhou
  • fYear
    2006
  • fDate
    26-29 Oct. 2006
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    A new approach to the improve chromosome, optimization by means of polynomial functional neural networks is presented. The functional neural networks contain four parameters that need to be optimized, the weight, training parameter, network topology and scaling factor, As a consequence, an accurate comparison with other optimization methods is needed. This paper presents a chromosome that are during the identification by means of optimization algorithm. Experiment result showed that the method is validity.
  • Keywords
    biology computing; cellular biophysics; neural nets; optimisation; chromosome recognition; optimization algorithm; polynomial functional neural networks; Artificial neural networks; Biological cells; Management training; Mathematics; Multidimensional systems; Network topology; Neural networks; Optimization methods; Polynomials; Space exploration;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Antennas, Propagation & EM Theory, 2006. ISAPE '06. 7th International Symposium on
  • Conference_Location
    Guilin
  • Print_ISBN
    1-4244-0162-3
  • Electronic_ISBN
    1-4244-0163-1
  • Type

    conf

  • DOI
    10.1109/ISAPE.2006.353279
  • Filename
    4168320