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
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;
Conference_Titel :
IEEE SoutheastCon 2010 (SoutheastCon), Proceedings of the
Conference_Location :
Concord, NC
Print_ISBN :
978-1-4244-5854-7
DOI :
10.1109/SECON.2010.5453833
