Abstract
This paper introduces the triangular fuzzy number (TFN)-valued gamma function and the T-Laplace transform, extending classical analytical operators to the TFN-valued functions. By leveraging a specialized component-wise structure for TFNs, we establish the fundamental properties and theoretical foundations of these transforms through rigorous proofs. The practical utility of the T-Laplace transform is demonstrated by solving fuzzy integro-differential equations within a T-electric circuit model. We demonstrate that for prescribed T-initial conditions, this framework maintains structural consistency throughout the transformation process. This enables the derivation of the TFN-valued analytical solution for the T-current, effectively modeling system uncertainty while preserving the characteristic TFN structure of the output.
| Original language | English |
|---|---|
| Pages (from-to) | 257-283 |
| Number of pages | 27 |
| Journal | Fuzzy Optimization and Decision Making |
| Volume | 25 |
| Issue number | 2 |
| DOIs | |
| State | Published - Jun 2026 |
Keywords
- T-laplace transform
- TFN-valued gamma function
- Triangular fuzzy number
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