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February 12, 2026Soft Computing0 citationsOpen Access

Analysis of solutions of fuzzy differential equations under the generalized derivative

FLFelipe LongoBLBeatriz LaiateMGMarta C. Gadotti

Key Points

  • The aim is to explore the solutions of fuzzy differential equations using a distinctive approach that involves generalized derivatives.
  • Introduced a corrected version of the fundamental theorem of calculus using g-differentiability.
  • Provided sufficient conditions for gH*-differentiability in fuzzy initial value problems.
  • Analyzed fuzzy processes that are g-differentiable and not gH or gH*-differentiable.
  • Established features of fuzzy differential equations solely relying on g-differentiability.
  • Clarified conditions under which certain fuzzy processes maintained g-differentiability.
  • Illustrated findings with examples related to Malthusian and Logistic models for population dynamics.

Abstract

Abstract The generalized derivative represents the broadest notion of the Hukuhara-type derivative of a fuzzy number-valued function in the literature. It exists for a wide class of fuzzy processes, since the generalized difference exists for any pair of fuzzy numbers. Despite its historical significance, few papers provide theoretical results on the g-derivative, primarily because of its complex analytical behavior. On the other hand, analyzing solutions to fuzzy differential equations from a comparative Hukuhara-type perspective allows establishing features of FDEs whose solutions are exclusively g-differentiable. The study begins by providing a corrected version of the fundamental theorem of calculus via the g-differentiability and Aumann integrability of a fuzzy function. Sufficient conditions over the field of a fuzzy initial value problem for the gH * -differentiability of the solutions are presented. Lastly, results on fuzzy processes derived from solutions of FDEs that are g-differentiable, but not gH, and not even gH * -differentiable, are given. Examples of population dynamics governed by the Malthusian and Logistic models are provided to illustrate different scenarios for the presented analysis.

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Cite This Study

Longo et al. (2026) studied this question.

synapsesocial.com/papers/698d6ebb5be6419ac0d5489bhttps://doi.org/10.1007/s00500-026-11183-4
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