Parallel LS-SVM for the numerical simulation of fractional Volterra’s population model

Alexandria Engineering Journal

A. Ghodsi¹  A.A. Aghaei²  M. Jani³  K. Parand⁴ 

[1] Corresponding author.;Department of Cognitive Modeling, Institute for Cognitive and Brain Sciences, Shahid Beheshti University, G.C. Tehran, Iran;Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Canada;Department of Computer Sciences, Faculty of Mathematical Sciences, Shahid Beheshti University, G.C. Tehran, Iran;

关键词: Least squares support vector machine;    Volterra’s population model;    Fractional derivative;    Collocation LS-SVR;    Parallel algorithm;   

DOI  :  

来源: DOAJ

【 摘 要 】

In this paper, we develop a least-squares support vector machine (LS-SVM) for solving a nonlinear fractional-order Volterra’s population model in a closed system. The fractional rational Legendre functions with an orthogonal property on a semi-infinite domain have been used as the kernel of LS-SVM. Learning the solution is done by solving a non-linear constrained optimization problem. To accelerate the learning process, we propose two different approaches based on the orthogonality of kernels and a shared-memory task parallelization scheme for multi-core systems. By carrying out several experiments, it is seen that the proposed approaches provide accurate solutions for fractional-order Volterra’s population model.

【 授权许可】

Unknown