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12-02-2018 | Methodologies and Application | Issue 11/2019

Soft Computing 11/2019

On fuzzy type-1 and type-2 stochastic ordinary and partial differential equations and numerical solution

Journal:
Soft Computing > Issue 11/2019
Authors:
Abhirup Bandyopadhyay, Samarjit Kar
Important notes
Communicated by V. Loia.

Abstract

This paper develops the mathematical framework and the solution of a system of type-1 and type-2 fuzzy stochastic differential equations (T1FSDE and T2FSDE) and fuzzy stochastic partial differential equations (T1FSPDE and T2FSPDE). The theory of fuzzy stochastic differential equations is developed with fuzzy initial values, fuzzy boundary values and fuzzy parameters. Some natural phenomena which perturbs randomly in the influence of a white noise can be modelled as stochastic dynamic systems whose initial conditions and/or parameters may be imprecise in nature as well. The imprecision of initial values and/or parameters is generally modelled by fuzzy sets. In this paper, the concept fuzzy stochastic differential equations is developed with the introduction of fuzzy stochastic process, fuzzy stochastic random variable and fuzzy Brownian motion. The generalized \(\hbox {L}^{\mathrm{p}}\)-integrability, based on the extension of the class of differentiable and integrable fuzzy functions, is applied and fuzzy stochastic differential equations are represented as fuzzy integral equations. A novel numerical scheme for simulations of fuzzy stochastic differential equations have also been developed. Some illustrative examples have been provided for different T1FSDE, T1FSPDE, T2FSDE and T2FSPDE models related to mathematical finance and problems in mathematical biology.

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