I have a stochastic differential equation, i.e, (for equation please click this link) https://math.stackexchange.com/questions/3064721/how-to-improve-the-convergence-of-a-stochastic-differential-equation

A, B, C and D are operators. we have one white noise and two color noises with specific correlation matrices. As we know that there are several methods to improve the convergence of a SDE, for example,

1) Decrease the number of noises

2) Use higher order numerical algorithms (Range Kutta etc.)

3) Use small time steps and large number of trajectories

Now, apart from above mentioned techniques, is there any other way to decrease the fluctuations of a SDE if we directly simulate it numerically with Euler or Range Kutta algorithms?