Global Optimization for Road Traffic Accident

Global Optimization for Road Traffic Accident | 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 Global Optimization for Road Traffic Accident Bulbula Kumeda Kussia, Ghanim ALWAN, Sadiq HUSSAIN, Maregu ASSEFA, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5310111/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 The exponential growth in road traffic accidents worldwide is resulting in severe difficulties in every scene of human life. The paper builds a reliable optimization frame to find the global minimum injury severity versus 20 attributes. A new method to find optimal values for the nonlinear frame of road traffic accidents was implemented here. To design and construct a reliable simulated model to improve the quality of the road traffic accident optimization process by using an advanced optimization technique. Even though the solving problems of non-linear optimization configuration were solved in some cases. The programming for solving optimization problems for 20 attributes is complicated; especially for integer constraints. Advanced work will be needed to achieve this task. Optimization aims to discover the values of a model's variables that produce the best value for the objective function, subject to any limiting conditions placed on the variables. The complexity of integer programming was solved based on good formulating of the integrated optimization model and the selection of a suitable matrix of constraints to avoid sharp changes for optimal results. Our experimental results show that Impactype (X8) and Invtype (X9) are still effective and sensitive attributes for injury severity. global optimization injury severity mixed-integer non-linear programming supervised learning optimization search Full Text Additional Declarations No competing interests reported. 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-5310111","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":372726887,"identity":"31733916-b0b0-408d-8de3-c587516430aa","order_by":0,"name":"Bulbula Kumeda Kussia","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzklEQVRIiWNgGAWjYBACAwY2EMXMwA+iEgpI0SLZANJiQIoWgwMQLmFgzt6WJnWjwlre+PzqxA8PDBjk+cUO4Ndi2XPsmHTOmXTDbTfebpYAOsxw5uwEAg67kd4mndt2mHHbjbMbQFoSDG4T0nL/OVDLv8P2m2ec3fyDOC032I5J5zYcTtzA37uNOFsse9KSrXOOpSfPuMG7zSLBQIKwX8zZjxnezqmxtu3vP7v55o8KG3l+aQJaEEACrFKCWOUgwH+AFNWjYBSMglEwkgAAFf5Fvz3fJ9EAAAAASUVORK5CYII=","orcid":"","institution":"Jinka University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Bulbula","middleName":"Kumeda","lastName":"Kussia","suffix":""},{"id":372726888,"identity":"fa8b7e77-7741-49f3-9460-5a61d23d91c7","order_by":1,"name":"Ghanim ALWAN","email":"","orcid":"","institution":"Missouri University of Science and Technology","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ghanim","middleName":"","lastName":"ALWAN","suffix":""},{"id":372726889,"identity":"81a9d1b2-adfb-4db9-8ce8-29b21af4b591","order_by":2,"name":"Sadiq HUSSAIN","email":"","orcid":"","institution":"Dibrugarh University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sadiq","middleName":"","lastName":"HUSSAIN","suffix":""},{"id":372726890,"identity":"4e79f6c2-bd3e-41c5-86c9-4cb96f461972","order_by":3,"name":"Maregu ASSEFA","email":"","orcid":"","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Maregu","middleName":"","lastName":"ASSEFA","suffix":""},{"id":372726891,"identity":"d0bc1007-f9bd-4764-aecc-1921df14efcd","order_by":4,"name":"Pranjal Kumar BORA","email":"","orcid":"","institution":"Dibrugarh University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Pranjal","middleName":"Kumar","lastName":"BORA","suffix":""}],"badges":[],"createdAt":"2024-10-22 08:53:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5310111/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5310111/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":74358040,"identity":"89941a8d-fc14-4b84-bd9e-624032173145","added_by":"auto","created_at":"2025-01-21 12:32:18","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":966946,"visible":true,"origin":"","legend":"","description":"","filename":"GlobalOptimizationforRoadTrafficAccidentDataSNOperationResearchForum.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5310111/v1_covered_0d95a527-d3fc-42fb-944f-f3fb28c7a88d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Global Optimization for Road Traffic Accident","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":"global optimization, injury severity, mixed-integer non-linear programming, supervised learning, optimization search","lastPublishedDoi":"10.21203/rs.3.rs-5310111/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5310111/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e The exponential growth in road traffic accidents worldwide is resulting in severe difficulties in every scene of human life. The paper builds a reliable optimization frame to find the global minimum injury severity versus 20 attributes. A new method to find optimal values for the nonlinear frame of road traffic accidents was implemented here. To design and construct a reliable simulated model to improve the quality of the road traffic accident optimization process by using an advanced optimization technique. Even though the solving problems of non-linear optimization configuration were solved in some cases. The programming for solving optimization problems for 20 attributes is complicated; especially for integer constraints. Advanced work will be needed to achieve this task. Optimization aims to discover the values of a model's variables that produce the best value for the objective function, subject to any limiting conditions placed on the variables. The complexity of integer programming was solved based on good formulating of the integrated optimization model and the selection of a suitable matrix of constraints to avoid sharp changes for optimal results. Our experimental results show that Impactype (X8) and Invtype (X9) are still effective and sensitive attributes for injury severity.\u003c/p\u003e","manuscriptTitle":"Global Optimization for Road Traffic Accident","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-04 14:54:49","doi":"10.21203/rs.3.rs-5310111/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":"cc2f2a3d-3b0f-4aef-b9e0-356d890aaa3b","owner":[],"postedDate":"November 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-01-21T12:24:06+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-04 14:54:49","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5310111","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5310111","identity":"rs-5310111","version":["v1"]},"buildId":"FbvkV6FR0MCFSLy54lSbu","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}