Ranking Z-numbers Using the Optimal Clustering Method (CZ-number)
Saeed Jafari
1
(
Department of Electrical Engineering, Bushehr Branch, Islamic Azad University, Bushehr, Iran
)
Mojtaba Najafi
2
(
Department of Electrical Engineering, Bushehr Branch, Islamic Azad University, Bushehr, Iran
)
Naghi Moaddabi Pirkolahchahi
3
(
Department of Electrical Engineering, Bushehr Branch, Islamic Azad University, Bushehr, Iran
)
Najmeh Cheraghi Shirazi
4
(
Department of Electrical Engineering, Bushehr Branch, Islamic Azad University, Bushehr, Iran
)
Keywords: Probability-possibility, Unsupervised clustering, Z-number, CZ number, Fuzzy.,
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.
- Using the unsupervised learning method in the optimal selection of expert opinions.
- Effectiveness of the proposed method in choosing the optimal opinions of experts in the conditions of large and complex data sets of expert opinions.
- Determining the optimal points to determine the points that make up the intervals of the Z-number.
- The use of any method or algorithm for unsupervised clustering of points forming the Z-number.
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