Abstract: Immersive virtual reality (VR) technology has become an essential tool in enhancing user experience across industries, particularly in furniture design. With the ability to provide realistic, interactive, and immersive environments, it significantly improves user engagement and decision-making in product design. However, existing analysis methods lack precision in evaluating user experience within VR environments. This study aims to develop a more accurate and efficient model for analyzing the application of immersive VR in future furniture design. By integrating the Artificial Rabbit Optimization (ARO) algorithm with Capsule Networks (CapsNet), this research enhances the evaluation of user experience in immersive VR environments. The proposed method uses the ARO algorithm to optimize the parameters of CapsNet, which maps the relationship between the analysis indicators of furniture design and user experience. This model is tested against traditional methods such as CNN and CapsNet alone. The analysis focuses on key factors such as visual elements, interaction, and system performance, with performance metrics like root mean square error (RMSE) and R² value used for evaluation. Experimental results show that the ARO-CapsNet model achieves a RMSE of 0.17 and an R² value of 0.988, outperforming both CNN and CapsNet in terms of accuracy and efficiency. Additionally, the proposed model improves the immersive VR system's ability to deliver accurate user experience evaluations, making it a superior method for analyzing future furniture design applications. The integration of the ARO algorithm with CapsNet significantly enhances the precision of immersive VR user experience evaluations in furniture design. The ARO-CapsNet model not only improves evaluation accuracy but also increases system efficiency, providing a robust framework for future applications of VR in product design.

Yin Luo, Jun Liu and Li Zhang, “ARO-CapsNet: A Novel Method for Evaluating User Experience in Immersive VR Furniture Design” International Journal of Advanced Computer Science and Applications(IJACSA), 15(11), 2024. http://dx.doi.org/10.14569/IJACSA.2024.0151125

@article{Luo2024,
title = {ARO-CapsNet: A Novel Method for Evaluating User Experience in Immersive VR Furniture Design},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2024.0151125},
url = {http://dx.doi.org/10.14569/IJACSA.2024.0151125},
year = {2024},
publisher = {The Science and Information Organization},
volume = {15},
number = {11},
author = {Yin Luo and Jun Liu and Li Zhang}
}