Research on civil aviation airport site selection considering group consensus level under large-scale uncertain information

Research on civil aviation airport site selection considering group consensus level under large-scale uncertain information | 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 Research Article Research on civil aviation airport site selection considering group consensus level under large-scale uncertain information Rui Wang, Jing-Han Zeng, Jing-Yang Huang, Rui Kang, Jiang Yuan, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5669394/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract In response to the decision-making challenges posed by large-scale information and complex data sources in civil aviation airport site selection, this paper proposes a novel method that integrates group consensus within a framework of substantial uncertainty. The method comprises five key processes: (1) Evaluation process: Based on the constructed multi-criteria evaluation system for airport site selection, the q-Rung Orthopair Fuzzy (q-ROF) information is employed to represent evaluations from large-scale decision makers, which effectively characterizes the uncertainty of information and broadens the evaluative scope. (2) Clustering process: A clustering procedure is designed for large-scale q-ROF evaluation data and weight information of criteria, identifying and removing outliers. (3) Consensus reaching process: Considering the characteristics of q-ROF evaluations and multiplicative preference relations, two adaptive consensus reaching algorithms are developed to enhance group consensus levels, thereby improving the rationality of decision-making results. (4) Weight determination process: Criteria and subcriteria weights are calculated using multiplicative preference weighting approach and a deviation maximization model, respectively, derived from aggregated group evaluations. (5) Ranking process: The q-ROF Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method is applied, in conjunction with the induced q-ROF information integration paradigm, to comprehensively rank the alternative sites. Finally, the feasibility and effectiveness of the proposed method are demonstrated through a case study of civil aviation branch airport planning in a specific city. civil aviation airport site selection large-scale uncertain information group consensus level q-rung orthopair fuzzy set clustering approach Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 05 Apr, 2025 Reviewers agreed at journal 03 Apr, 2025 Reviewers agreed at journal 30 Mar, 2025 Reviews received at journal 29 Mar, 2025 Reviewers agreed at journal 29 Mar, 2025 Reviewers invited by journal 29 Mar, 2025 Submission checks completed at journal 28 Mar, 2025 First submitted to journal 23 Mar, 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5669394","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":436029511,"identity":"e471e718-7a17-4449-828f-be7f0765217e","order_by":0,"name":"Rui 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