Title :
Support vector regression method for boundary value problems
Author :
Fu, Kun ; Wang, You-hua ; Dong, Yong-Feng ; Hou, Xiang-Dan ; Shen, Xue-Qin ; Yan, Wei-li
Author_Institution :
Hebei Univ. of Technol., TianJin, China
Abstract :
This article presents a method to solve boundary value problems using support vector regression and radial basis function network. The boundary is determined by a number of points that belong to it and are closely located, so as to offer a reasonable representation. Two methods are employed: a support vector regression is constructed to have part of effect on the boundary conditions as the basic approximate element and contains adjustable parameters; a radial basis function network is used to account for the exact satisfaction of the boundary conditions. The method was used to solve a two-dimensional partial differential equation and had gained feasible accurate result. This method is completely practical in technology.
Keywords :
boundary-value problems; partial differential equations; radial basis function networks; regression analysis; support vector machines; 2D partial differential equation; boundary condition; boundary value problems; radial basis function network; support vector machine; support vector regression; Boundary conditions; Boundary value problems; Constraint optimization; Differential equations; Electronic mail; Machine learning; Partial differential equations; Radial basis function networks; Shape; Support vector machines; Support vector regression; boundary value problems; partial differential equation radial basis function network; support vector machine;
Conference_Titel :
Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on
Conference_Location :
Guangzhou, China
Print_ISBN :
0-7803-9091-1
DOI :
10.1109/ICMLC.2005.1527692
