A Novel Approach for Individual Design Perception Based on Fuzzy Inference System Training with YUKI Algorithm

This paper presents a novel approach for individual design perception modeling using the YUKI algorithm-trained Fuzzy Inference System. The study focuses on understanding how individuals perceive based personality traits, particularly openness to experience, algorithm and C-means clustering algorithm. generates several Sugeno-type System models predict perception, minimize Root Mean Squared Error between model prediction actual of participants. results demonstrate that suggested method offers more accurate predictions compared traditional Deep Artificial Neural Networks, Square deviation perceptions falls within satisfactory range 0.84 1.32. proves effective in their level openness, providing insights into traits influence perception.