Open AccessWong-Zakai method for stochastic differential equations in engineering
Author(s) -
Süleyman Şengül,
Zafer Bekiryazıcı,
Mehmet Merdan
Publication year - 2021
Publication title -
thermal science/thermal science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.339
H-Index - 43
eISSN - 2334-7163
pISSN - 0354-9836
DOI - 10.2298/tsci200528014s
Subject(s) - stochastic partial differential equation , stochastic differential equation , euler method , numerical partial differential equations , mathematics , euler equations , examples of differential equations , backward differentiation formula , differential equation , differential algebraic equation , computer science , mathematical analysis , ordinary differential equation
In this paper, Wong-Zakai approximation methods are presented for some stochastic differential equations in engineering sciences. Wong-Zakai approximate solutions of the equations are analyzed and the numerical results are compared with results from popular approximation schemes for stochastic differential equations such as Euler-Maruyama and Milstein methods. Several differential equations from engineering problems containing stochastic noise are investigated as numerical examples. Results show that Wong-Zakai method is a reliable tool for studying stochastic differential equations and can be used as an alternative for the known approximation techniques for stochastic models.