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Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines | IEEE Journals & Magazine | IEEE Xplore

Approximate Solutions to Ordinary Differential Equations Using Least Squares Support Vector Machines

Publisher: IEEE

Abstract:

In this paper, a new approach based on least squares support vector machines (LS-SVMs) is proposed for solving linear and nonlinear ordinary differential equations (ODEs)...View more

Abstract:

In this paper, a new approach based on least squares support vector machines (LS-SVMs) is proposed for solving linear and nonlinear ordinary differential equations (ODEs). The approximate solution is presented in closed form by means of LS-SVMs, whose parameters are adjusted to minimize an appropriate error function. For the linear and nonlinear cases, these parameters are obtained by solving a system of linear and nonlinear equations, respectively. The method is well suited to solving mildly stiff, nonstiff, and singular ODEs with initial and boundary conditions. Numerical results demonstrate the efficiency of the proposed method over existing methods.
Published in: IEEE Transactions on Neural Networks and Learning Systems ( Volume: 23, Issue: 9, September 2012)
Page(s): 1356 - 1367
Date of Publication: 22 June 2012

ISSN Information:

PubMed ID: 24807921
Publisher: IEEE

References

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