Design of Panoramic Virtual Museum Interactive Interface Based on Entropy Weight TOPSIS and PSO-SVR

Design of Panoramic Virtual Museum Interactive Interface Based on Entropy Weight TOPSIS and PSO-SVR | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Design of Panoramic Virtual Museum Interactive Interface Based on Entropy Weight TOPSIS and PSO-SVR Zikai Wang, Fang Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5526948/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 21 May, 2025 Read the published version in npj Heritage Science → Version 1 posted 6 You are reading this latest preprint version Abstract This study addresses the neglect of user emotional needs in digital cultural heritage displays by proposing a quantitative methodology to optimize the Panoramic Virtual Museum Interactive Interface (PVMUI). Leveraging Kansei Engineering, we first extracted three core affective dimensions (Technological, Innovative, Fancy) through factor analysis of 45 Kansei terms. Morphological decomposition and entropy-weighted TOPSIS objectively prioritized six critical design features from 14 candidates. A nonlinear mapping model integrating Particle Swarm Optimization Support Vector Regression (PSO-SVR) was developed to correlate these features with user emotions, validated empirically via 100 participants. Results identified an optimal configuration: top-bottom layout (A1-1), 30% screen occupancy (A2-3), transparent navigation icons (A5-5), planar maps (A7-3), arrow-shaped movement icons (A9-7), and no scene interaction (A10-6). The framework advances virtual museum design by establishing emotion-driven optimization principles, bridging theoretical gaps in affective computing for PVMUI while offering actionable guidelines for enhancing user immersion and heritage dissemination. Panoramic Virtual Museum (PVM) Interactive Interface Design Kansei Engineering Entropy Weight TOPSIS Particle Swarm Optimization Support Vector Regression (PSO-SVR) Emotional Identification Full Text Additional Declarations No competing interests reported. Supplementary Files SupplementaryData1.xlsx SupplementaryData2.xlsx SupplementaryData3.xls SupplementaryData4.xlsx SupplementaryData5.xlsx SupplementaryData6.xlsx SupplementaryInformation.pdf Cite Share Download PDF Status: Published Journal Publication published 21 May, 2025 Read the published version in npj Heritage Science → Version 1 posted Editorial decision: Accepted 29 Apr, 2025 Reviews received at journal 25 Apr, 2025 Reviewers agreed at journal 05 Apr, 2025 Reviewers invited by journal 05 Apr, 2025 Submission checks completed at journal 05 Apr, 2025 First submitted to journal 19 Feb, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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