A new class of stochastic Runge–Kutta (SRK) methods for the strong approximation of Stratonovich stochastic ordinary differential equations (SODEs) is presented. The proposed method is an alternative to the method of Xiao and Tang (Numer. Algor. 72: 259–296, 2016) and converges with order 2 in the strong sense. To validate the efficiency and to compare with some known methods, numerical simulations which involve generating Stratonovich stochastic integrals of level 3, are finally given.

中文翻译：

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具有标量噪声的Stratonovich随机微分方程的强逼近的显式2格式

提出了用于Stratonovich随机常微分方程（SODE）的强逼近的一类新的随机Runge-Kutta（SRK）方法。所提出的方法是Xiao和Tang（Numer。Algor。72：259-296，2016）的替代方法，并且在强烈意义上收敛于2阶。为了验证效率并与一些已知方法进行比较，最后给出了涉及生成3级Stratonovich随机积分的数值模拟。