Work

Ranking Z-numbers Using the Optimal Clustering Method (CZ-number)

Year: 2025

Type: article

Abstract: In recent years, modeling uncertainties through natural language has attracted growing attention, with Z-numbers, introduced by Zadeh in 2011, being a key concept. A Z-number consists of two fuzzy components: the first represents the possibility of an event’s occurrence, while the second expresses the probability of that occurrence. A major challenge in applying Z-numbers lies in properly structuring these two components; inappropriate strategies can lead to inaccurate results, especially in group decision-making contexts with large data volumes. To address this, the paper proposes an optimal clustering approach for structuring the components of Z-numbers more systematically and purposefully. This method enhances the accuracy of Z-number modeling by reducing errors in component formation. The effectiveness of the proposed approach is validated through a comparison with conventional fuzzy methods, demonstrating improved performance in handling uncertainty.

Source: DOAJ (DOAJ: Directory of Open Access Journals)

Authors: Saeed Jafari, Mojtaba Najafi, Naghi Moaddabi Pirkolahchahi, Najmeh Cheraghi Shirazi

Institution: Islamic Azad University, Bushehr Branch

Language: English

Topic: Multi-Criteria Decision Making

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

Open Access status: green

OpenAlex ID: W7090618865

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