Authors : Yolam Sakala; Hamilton Chirwa; Elias Muma

Volume/Issue : Volume 10 - 2025, Issue 6 - June

Google Scholar : https://tinyurl.com/3v5fcwwh

DOI : https://doi.org/10.38124/ijisrt/25jun1025

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The dual nature of uncertainty, which encompasses both vagueness and hesitation, is frequently not captured by conventional fuzzy systems. In the context of fuzzy differential equations (FDEs), this paper presents a sophisticated mathematical framework that combines intuitionistic fuzzy sets (IFSs) and fuzzy choquet integrals. By adding degrees of membership, non-membership, and hes- itation, IFSs expand on the traditional fuzzy paradigm. Meanwhile, the Fuzzy Choquet Integral al- lows for the aggregation of interdependent data, going beyond the constraints of additive measures. We show that our method can be applied to dynamic systems, develop a generalized solution the- ory for fuzzy differential equations under intuitionistic uncertainty, and provide simulation-based validations. The framework creates new opportunities in domains like finance, health systems, and environmental modelling where complicated, ambiguous, and hesitant information predominates.

Keywords : Intuitionistic Fuzzy Sets, Fuzzy Choquet Integral, Fuzzy Differential Equations, Un- Certainty Modeling, Dynamic Systems Simulation.

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