{"paper_id":"4d42e215-da97-4bd7-a703-e36ff855ae08","body_text":"A Harris Hawks optimization-based cellular automata model for urban growth simulation | 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 A Harris Hawks optimization-based cellular automata model for urban growth simulation Yuan Ding, Hengyi Zheng, Fuming Jin, Dongming Chen, Xinyu Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4636601/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jul, 2024 Read the published version in Earth Science Informatics → Version 1 posted You are reading this latest preprint version Abstract This paper proposes an innovative cellular automata model based on the Harris Hawk Optimization (HHO) algorithm. HHO is an intelligent optimization algorithm inspired by the cooperative hunting behavior of Harris's hawks, demonstrating excellent optimization efficiency in spatial searches. Combining the HHO algorithm with the CA model, we establish the HHO-CA model for simulating urban growth in Guangzhou, China. The simulation achieves a total accuracy of 91.95%, an accuracy of urban cells of 82.43%, and a Kappa coefficient of 0.7441, all superior to the Null model. Furthermore, comparing the HHO-CA model with other representative CA models, the HHO-CA model outperforms in total accuracy, accuracy of urban cells, and Kappa coefficient, showcasing significant advantages in using the HHO algorithm to mine transition rules during the simulation of urban growth processes. Urban Studies Geographic Information Systems urban growth Harris Hawks optimization cellular automata transition rules mining spatial dynamic simulation Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Published Journal Publication published 05 Jul, 2024 Read the published version in Earth Science Informatics → Version 1 posted 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. 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