Fuzzy Systems and its Applications

Fuzzy Systems and its Applications

Prioritizing face editing models using fuzzy hierarchical analysis

Document Type : Original Article

Authors
1 Computer Engineering, Engineering Technology, Shahid Bahoner, Kerman, Iran
2 0
10.22034/jfsa.2026.561816.1293
Abstract
This study aimed to prioritize face editing models based on adversarial generative networks through evidence-based fuzzy analytic hierarchy process to provide a transparent, repeatable, and data-driven framework for selecting the optimal model in practical applications. To achieve this goal, first, 8 main criteria and 24 sub-criteria were extracted through a systematic review of 42 scientific articles (2018–2024) and organized into a four-level hierarchical structure. The criteria were weighted using a fuzzy pairwise comparison matrix and a combination of 70% quantitative data and 30% judgment of three expert experts. The calculations were implemented completely manually in Python using the Buckley algorithm (1985), and the consistency of the judgments was confirmed with a CR index of 0.078 (less than 0.1). The results showed that the latent space interpretation model of generative adversarial networks for semantic face editing and the feature-based adversarial generative network model for facial feature editing ranked first and second with final weights of 0.312 and 0.308, respectively, while feature control accuracy with a weight of 0.178, continuous editing with 0.153, and inference speed with 0.139 were identified as key criteria. Sensitivity analysis also confirmed the stability of the rankings. These findings suggest that focusing on functional and operational criteria can lead to the design of more efficient and deployable models in real systems.
Keywords
Subjects

 
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Volume 8, Issue 2 - Serial Number 17
Open Access Statement
December 2025
Pages 251-273

  • Receive Date 24 November 2025
  • Revise Date 27 January 2026
  • Accept Date 19 February 2026