Estimating the travel distance of channelized rock avalanches using genetic programming and support vector machine

Estimating the travel distance of channelized rock avalanches using genetic programming and support vector machine | 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 Estimating the travel distance of channelized rock avalanches using genetic programming and support vector machine Yong Zhang, Tao Wang, Mei Liu, Mingfeng Deng, Ningsheng Chen, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3780436/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Channelized rock avalanche travel distance (CRATD) is one of key parameters in disaster risk analysis. Although traditional regression analysis methods is widely used in estimating CRATD, there is lack of studies on whether there is a room for further improvement. In this study, 34 channelized rock avalanche events triggered by Wenchuan earthquake in Fujiang River Basin were assembled to develop a robust model for estimating CRATD using two machine learning methods (Genetic Programming (GP) and Support Vector Machine (SVM)) and a widely accepted traditional regression analysis method (Power Form model (PFM)). It was found that GP model performed best among the three methods when the influence of source area, height difference between the head scarp crown and the base of the collapsed slope, average inclination angle of the source zone, and average slope angle of the travel path on the travel distance were considered in GP model. The proposed GP model was verified and compared against six previous models using 15 channelized rock avalanche events induced by Wenchuan earthquake in Tuojiang River Basin. The proposed GP model shows significant improvement in estimating CRATD. In view of the limited number of channelized rock avalanche events, the application range of the proposed GP model is suggested. In conclusion, the proposed GP model could play a beneficial role in related disaster prevention and land management. channelized rock avalanche travel distance genetic programming support vector machine Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Full Text Additional Declarations Tables 1 to 5 are available in the Supplementary Files section. Supplementary Files CRATDTable.doc Cite Share Download PDF Status: Posted 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. 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-3780436","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":266397190,"identity":"62f7f3f6-e50d-4685-af4d-1b01b68a9386","order_by":0,"name":"Yong Zhang","email":"","orcid":"","institution":"Anyang Institute of Technology","correspondingAuthor":false,"prefix":"","firstName":"Yong","middleName":"","lastName":"Zhang","suffix":""},{"id":266397191,"identity":"9a3658e7-444e-4d94-a1b8-2b2dd5242e6d","order_by":1,"name":"Tao 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19:19:44","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":8102313,"visible":true,"origin":"","legend":"\u003cp\u003eRemote sensing images of Baishuling channelized rock avalanche triggered by the Wenchuan earthquake (104°23'6.00\"E 31°48'25.20\"N)\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/a63e8609fe06aea8ac453a13.jpeg"},{"id":49547249,"identity":"6c74f1d6-f22e-4d6a-9259-5e4c4c67acde","added_by":"auto","created_at":"2024-01-12 19:19:43","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1499444,"visible":true,"origin":"","legend":"\u003cp\u003eChannelized rock avalanches including definitions of relevant geometric parameters (modified from Davies, 1989)\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/111899c87f97a53bdccd5da0.jpeg"},{"id":49547256,"identity":"88a0719e-cbe7-4e95-bfbc-e9529c4d7b68","added_by":"auto","created_at":"2024-01-12 19:19:44","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2719572,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the coefficient of efficiency (\u003cem\u003eE\u003c/em\u003e\u003csub\u003e\u003cem\u003esn\u003c/em\u003e\u003c/sub\u003e) for all three models: (a) genetic programming (GP) model; (b) support vector machine (SVM) model; (c) power form model (PFM) model; (d) legend\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/52a292d5b8ff553d54ec0874.jpeg"},{"id":49548046,"identity":"4b92f7ef-84f3-4c44-a0e4-2111f2c4b131","added_by":"auto","created_at":"2024-01-12 19:27:44","extension":"jpeg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":1396584,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of the prediction error (\u003cem\u003eMAPE\u003c/em\u003e) for all three models: (a) GP model; (b) SVM model; (c) PFM model; (d) legend\u003c/p\u003e","description":"","filename":"floatimage5.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/ca1aca12a5c59295ba584daa.jpeg"},{"id":49547254,"identity":"b5680461-7d3a-4ef2-953a-72d75393f0a6","added_by":"auto","created_at":"2024-01-12 19:19:44","extension":"jpeg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1969441,"visible":true,"origin":"","legend":"\u003cp\u003eComparison between estimated and observed travel distance for the optimal GP model\u003c/p\u003e","description":"","filename":"floatimage6.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/8917ef7f3b9d8e576672e02c.jpeg"},{"id":49547251,"identity":"27288245-c7c3-41a2-ba1b-b59dd7d72f9b","added_by":"auto","created_at":"2024-01-12 19:19:44","extension":"jpeg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":1878177,"visible":true,"origin":"","legend":"\u003cp\u003eComparison between estimated and observed travel distances for the optimal SVM model\u003c/p\u003e","description":"","filename":"floatimage7.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/7ab5544a06114f2d711f14e7.jpeg"},{"id":49548580,"identity":"6d7f2349-a5ca-4a4c-a65b-4b7fe6fa1fb3","added_by":"auto","created_at":"2024-01-12 19:35:44","extension":"jpeg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":1946254,"visible":true,"origin":"","legend":"\u003cp\u003eComparison between estimated and observed travel distances for the optimal PFM model\u003c/p\u003e","description":"","filename":"floatimage8.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/7e83b7075969ddafb0107057.jpeg"},{"id":49547255,"identity":"6b0726c0-6a30-4bef-ad5c-4e663d0926ce","added_by":"auto","created_at":"2024-01-12 19:19:44","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":569866,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of CRATDestimations using previously published equations and proposed GP model: (a) Davies et al. (1982); (b) Legros (2002); (c) Jaiswal et al. (2011); (d) Qi et al. (2011); (e) Zhan et al. (2017); (f) Strom et al. (2019); (g) Mitchell et al. (2019); and (h) proposed GP mode.\u003c/p\u003e","description":"","filename":"floatimage9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/fe408a2f3c34137ffd1e70d6.jpeg"},{"id":50396465,"identity":"b78a371a-4990-4fd6-b69c-5a9bfeef67df","added_by":"auto","created_at":"2024-01-30 23:28:42","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1129758,"visible":true,"origin":"","legend":"","description":"","filename":"CRATDmainmanuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1_covered_53e8659a-dd07-420a-9650-37141ca7676d.pdf"},{"id":49547248,"identity":"1763022c-9ddf-4c7f-a920-f34c913f9485","added_by":"auto","created_at":"2024-01-12 19:19:43","extension":"doc","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":144354,"visible":true,"origin":"","legend":"","description":"","filename":"CRATDTable.doc","url":"https://assets-eu.researchsquare.com/files/rs-3780436/v1/ffcdbe20c50fa2d41a235027.doc"}],"financialInterests":"\u003cp\u003eTables 1 to 5 are available in the Supplementary Files section.\u003c/p\u003e","formattedTitle":"Estimating the travel distance of channelized rock avalanches using genetic programming and support vector machine","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"channelized rock avalanche, travel distance, genetic programming, support vector machine","lastPublishedDoi":"10.21203/rs.3.rs-3780436/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3780436/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Channelized rock avalanche travel distance (CRATD) is one of key parameters in disaster risk analysis.\nAlthough traditional regression analysis methods is widely used in estimating CRATD, there is lack of studies on whether there is a room for further improvement. In this study, 34 channelized rock avalanche events triggered by Wenchuan earthquake in Fujiang River Basin were assembled to develop a robust model for estimating CRATD using two machine learning methods (Genetic Programming (GP) and Support Vector Machine (SVM)) and a widely accepted traditional regression analysis method (Power Form model (PFM)). It was found that GP model performed best among the three methods when the influence of source area, height difference between the head scarp crown and the base of the collapsed slope, average inclination angle of the source zone, and average slope angle of the travel path on the travel distance were considered in GP model. The proposed GP model was verified and compared against six previous models using 15 channelized rock avalanche events induced by Wenchuan earthquake in Tuojiang River Basin. The proposed GP model shows significant improvement in estimating CRATD. In view of the limited number of channelized rock avalanche events, the application range of the proposed GP model is suggested. In conclusion, the proposed GP model could play a beneficial role in related disaster prevention and land management.","manuscriptTitle":"Estimating the travel distance of channelized rock avalanches using genetic programming and support vector machine","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-12 19:19:39","doi":"10.21203/rs.3.rs-3780436/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"11c15e18-1866-4d34-a38c-9a884bc2a608","owner":[],"postedDate":"January 12th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-01-30T23:20:28+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-12 19:19:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3780436","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3780436","identity":"rs-3780436","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}