• DocumentCode
    2197741
  • Title

    A genetic algorithm approach to the solution of a differential equation

  • Author

    MacNeil, Paul E. ; Schultz, Scott R.

  • Author_Institution
    Sch. of Eng., Mercer Univ., Macon, GA, USA
  • fYear
    2010
  • fDate
    18-21 March 2010
  • Firstpage
    448
  • Lastpage
    450
  • Abstract
    This paper proposes an approach to solving differential equations by using a genetic algorithm to adjust parameter values in candidate solutions so as to minimize the sum squared error of the differential equation. An example solution is developed for a differential equation representing an electron in the Coulomb potential of two protons. Two measurable parameter values are estimated via this process and compared with published values.
  • Keywords
    differential equations; genetic algorithms; mean square error methods; Coulomb potential; differential equation; genetic algorithm; mean sum square error; Atomic measurements; Biological cells; Differential equations; Eigenvalues and eigenfunctions; Electrons; Genetic algorithms; Genetic engineering; Genetic mutations; H infinity control; Protons;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IEEE SoutheastCon 2010 (SoutheastCon), Proceedings of the
  • Conference_Location
    Concord, NC
  • Print_ISBN
    978-1-4244-5854-7
  • Type

    conf

  • DOI
    10.1109/SECON.2010.5453833
  • Filename
    5453833