Accelerated Genetic Algorithm Solutions Of Some Parametric Families Of Stochastic Differential Equations
Eman Ali Hussain, Yaseen Merzah Alrajhi
Index Terms: accelerated genetic algorithm, stochastic differential equations, Ito formula
Absract: In this project, A new method for solving Stochastic Differential Equations (SDEs) deriving by Wiener process numerically will be construct and implement using Accelerated Genetic Algorithm (AGA). An SDE is a differential equation in which one or more of the terms and hence the solutions itself is a stochastic process. Solving stochastic differential equations requires going away from the recognizable deterministic setting of ordinary and partial differential equations into a world where the evolution of a quantity has an inherent random component and where the expected behavior of this quantity can be described in terms of probability distributions. We applied our method on the Ito formula which is equivalent to the SDE, to find approximation solution of the SDEs. Numerical experiments illustrate the behavior of the proposed method.
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