DocumentCode
589254
Title
Numerical Solution of Dirichlet Boundary Value Problems for Partial Differential Equations Using Quantum-Behaved Particle Swarm Optimization with Random Gaussian Function
Author
Youngmin Ha
Author_Institution
Rackham Grad. Sch., Univ. of Michigan, Ann Arbor, MI, USA
Volume
1
fYear
2012
fDate
12-15 Dec. 2012
Firstpage
675
Lastpage
680
Abstract
A new mesh-based algorithm to solve partial differential equations (PDEs) using quantum-behaved particle swarm optimization (QPSO) with random Gaussian function and random median filter is proposed in this paper. The random Gaussian function behaves as a mutation operator of QPSO to escape from local minima, and the random median filter accelerates the convergence of QPSO. It provides accurate results for Dirichlet boundary value problems of both linear and nonlinear single PDEs in two space dimensions.
Keywords
Gaussian processes; boundary-value problems; computational complexity; convergence of numerical methods; median filters; mesh generation; partial differential equations; particle swarm optimisation; random processes; Dirichlet boundary value problems; QPSO convergence; linear single PDE; local minima; mesh-based algorithm; mutation operator; nonlinear single PDE; numerical solution; partial differential equations; quantum-behaved particle swarm optimization; random Gaussian function; random median filter; Boundary conditions; Genetic algorithms; Particle swarm optimization; Random variables; Sociology; Statistics; artificial intelligence; computational intelligence; evolutionary computation; partial differential equation; quantum-behaved particle swarm optimization;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Applications (ICMLA), 2012 11th International Conference on
Conference_Location
Boca Raton, FL
Print_ISBN
978-1-4673-4651-1
Type
conf
DOI
10.1109/ICMLA.2012.126
Filename
6406647
Link To Document