Global Journal of Engineering and Technology Research (GJETR) · Research article · Open access
On the Measures of Possibility and Probability of Uncertainty: A Fuzzy Theoretical Approach
David E. Nwanze, Cletus Onwubuoya, Ken Onyenike
3 December 2025 · Vol. 1, Issue 4, pp. 174-179
DOI: 10.65150/EP-gjetr/V1E4/2025-02
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What is this article about?
Uncertainty remains one of the most fundamental challenges in science, philosophy, and artificial intelligence (AI). Classical probability theory provides a means to quantify randomness, while possibility theory offers a way to describe vagueness and incomplete information.
Article at a glance
- Published
- 3 December 2025
- Volume / issue / pages
- Vol. 1, Issue 4, pp. 174-179
- ISSN
- 3051-3782 (online) · 3051-3774 (print)
- Licence
- CC BY 4.0 — free to read and reuse with attribution
- Peer review
- Double-blind, at least two independent reviewers
- Publisher
- EP Journals Group
Abstract
Uncertainty remains one of the most fundamental challenges in science, philosophy, and artificial intelligence (AI). Classical probability theory provides a means to quantify randomness, while possibility theory offers a way to describe vagueness and incomplete information. This paper explores the theoretical measures of possibility and probability within the fuzzy theoretical framework, focusing on their conceptual distinctions, mathematical relationships, and integrative potential. Drawing on developments in fuzzy set theory, this study recognizes the complementary roles of possibility and probability measures in modelling uncertainty and decision-making systems. It therefore, proposes a hybrid uncertainty representation that unites probabilistic and possibilistic reasoning. Applications in environmental risk analysis and decision systems demonstrate how fuzzy theory that bridges the gap between quantitative and qualitative uncertainty. The results contribute to a unified understanding of uncertainty representation and reasoning under imprecise conditions. The analysis highlights the implications of these measures of uncertainty in reasoning, risk assessment and intelligent system design.
Keywords: Fuzzy logic, possibility theory, probability theory, uncertainty modeling, epistemic uncertainty, risk analysis
Cite this article
David E. Nwanze, Cletus Onwubuoya, & Ken Onyenike (2025). On the Measures of Possibility and Probability of Uncertainty: A Fuzzy Theoretical Approach. Global Journal of Engineering and Technology Research, 1(4), 174-179. https://doi.org/10.65150/EP-gjetr/V1E4/2025-02
@article{David2025,
title = {On the Measures of Possibility and Probability of Uncertainty: A Fuzzy Theoretical Approach},
author = {David E. Nwanze and Cletus Onwubuoya and Ken Onyenike},
journal = {Global Journal of Engineering and Technology Research},
year = {2025},
volume = {1},
number = {4},
pages = {174-179},
doi = {10.65150/EP-gjetr/V1E4/2025-02},
url = {https://doi.org/10.65150/EP-gjetr/V1E4/2025-02}
}Questions about this article
Who wrote this article?
David E. Nwanze, Cletus Onwubuoya, Ken Onyenike.
Where and when was it published?
In Global Journal of Engineering and Technology Research, Volume 1, Issue 4, pages 174-179, published by EP Journals Group on 3 December 2025.
Is this article free to read?
Yes. It is open access under a Creative Commons Attribution 4.0 (CC BY 4.0) licence, so anyone can read, share and reuse it with attribution.
What is the DOI of this article?
10.65150/EP-gjetr/V1E4/2025-02 (https://doi.org/10.65150/EP-gjetr/V1E4/2025-02).
How do I cite this article?
APA: David E. Nwanze, Cletus Onwubuoya, & Ken Onyenike (2025). On the Measures of Possibility and Probability of Uncertainty: A Fuzzy Theoretical Approach. Global Journal of Engineering and Technology Research, 1(4), 174-179. https://doi.org/10.65150/EP-gjetr/V1E4/2025-02
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