Perceptual Intention Seat Design and Its Applicability Based on KE-PSO-SVR Model

TANG Fanxi; YANG Qin; GAO Shangqing

doi:10.19554/j.cnki.1001-3563.2025.12.045

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Packaging Engineering ›› 2025, Vol. 46 ›› Issue (12) : 449-459. DOI: 10.19554/j.cnki.1001-3563.2025.12.045

Design Discussion

Perceptual Intention Seat Design and Its Applicability Based on KE-PSO-SVR Model

TANG Fanxi¹, YANG Qin², GAO Shangqing^2*

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Abstract

The work aims to apply a new design research framework and combine machine learning algorithms to provide sustainable design method guidance for seat design. Through quantization of characteristics of seats and the emotional cognition of users, a clear mapping relationship was established between the two using Kansei Engineering (KE). Subsequently, the PSO-SVR (Support Vector Regression with Optimized Particle Swarm Optimization) model was used to explore the nonlinear correlation between seat features and user emotional cognition, fit the optimal curve, and finally conduct experiments based on the trained model to accurately predict user emotional cognition. The seat designed with the KE-PSO-SVR model could accurately and efficiently capture the nonlinear relationship between user cognition and seat features, which can better and effectively meet design requirements and improve user satisfaction. This design model injects a new perspective into the field of furniture design and provides a certain reference basis for furniture design innovation.

Key words

perceptual image / seat design / user needs / Kansei engineering / support vector regression

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TANG Fanxi, YANG Qin, GAO Shangqing. Perceptual Intention Seat Design and Its Applicability Based on KE-PSO-SVR Model[J]. Packaging Engineering. 2025, 46(12): 449-459 https://doi.org/10.19554/j.cnki.1001-3563.2025.12.045

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