基于RK-LS-SVM求常微分方程的近似解OA

A RK-LS-SVM method combining the Runge-Kutta(RK)method with the least squares support vector machine(LS-SVM)was proposed to approximate the initial value problem of linear ordi-nary differential equations.Firstly,the numerical solution of the differential equation was obtained through the fourth-order Runge-Kutta method.Then,this numerical solution was transformed into the constraint conditions of the LS-SVM regression model,and the optimization problem was solved.The obtained approximate solution in closed form was continuously differentiable with high accuracy.Nu-merical examples have verified the effectiveness and feasibility of this method.