Qualitative analysis of symmetric fuzzy stochastic differential equations

In this paper, a special approach to stochastic differential equations is explored. Specifically, the values of the mappings involved are fuzzy sets, rather than the usual single values on the real line. Additionally, the equations under consideration are symmetric, meaning that the terms of drift and diffusion appear on both sides of the equation, which is crucial for the properties of the solutions. The primary goal of this paper is to establish certain qualitative results, such as the existence of a unique solution and stability of the solution. These results are obtained under the assumption that the coefficients of the equation satisfy a condition that is weaker than the standard Lipschitz condition. It is also noted that the results obtained can be applied to symmetric fuzzy random integral equations and deterministic symmetric fuzzy integral equations.

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Publication Details

Journal
International Journal of Applied Mathematics and Computer Science
Published
2025-01-01
DOI
https://doi.org/10.61822/amcs-2025-0028
Citations
1
Primary Topic
Fuzzy Systems and Optimization
Type
article
Field-Weighted Citation Impact
2.63
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article

Qualitative analysis of symmetric fuzzy stochastic differential equations

Marek T. Malinowski
1 citations
International Journal of Applied Mathematics and Computer Science
Fuzzy Systems and Optimization
2.63
article

Qualitative analysis of symmetric fuzzy stochastic differential equations

Marek T. Malinowski
article en
1 citations

Abstract

In this paper, a special approach to stochastic differential equations is explored. Specifically, the values of the mappings involved are fuzzy sets, rather than the usual single values on the real line. Additionally, the equations under consideration are symmetric, meaning that the terms of drift and diffusion appear on both sides of the equation, which is crucial for the properties of the solutions. The primary goal of this paper is to establish certain qualitative results, such as the existence of a unique solution and stability of the solution. These results are obtained under the assumption that the coefficients of the equation satisfy a condition that is weaker than the standard Lipschitz condition. It is also noted that the results obtained can be applied to symmetric fuzzy random integral equations and deterministic symmetric fuzzy integral equations.

International Journal of Applied Mathematics and Computer ScienceVol. 35(3)
Openalex Percentile: Top 9%
Fuzzy Systems and Optimization
2.63
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