ŞEHİR e-arşiv

Investigating injury severity risk factors in automobile crashes with predictive analytics and sensitivity analysis methods

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dc.contributor.author Delen, Dursun
dc.contributor.author Tomak, Leman
dc.contributor.author Topuz, Kazim
dc.contributor.author Eryarsoy, Enes
dc.date.accessioned 2017-09-21T14:14:07Z
dc.date.available 2017-09-21T14:14:07Z
dc.date.issued 2017
dc.identifier.issn 2214-1413
dc.identifier.uri http://www.sciencedirect.com/science/article/pii/S2214140516302389?via%3Dihub
dc.identifier.uri http://hdl.handle.net/11498/43727
dc.description.abstract Investigation of the risk factors that contribute to the injury severity in motor vehicle crashes has proved to be a thought-provoking and challenging problem. The results of such investigation can help better understand and potentially mitigate the severe injury risks involved in automobile crashes and thereby advance the well-being of people involved in these traffic accidents. Many factors were found to have an impact on the severity of injury sustained by occupants in the event of an automobile accident. In this analytics study we used a large and feature-rich crash dataset along with a number of predictive analytics algorithms to model the complex relationships between varying levels of injury severity and the crash related risk factors. Applying a systematic series of information fusion-based sensitivity analysis on the trained predictive models we identified the relative importance of the crash related risk factors. The results provided invaluable insights for the use of predictive analytics in this domain and exposed the relative importance of crash related risk factors with the changing levels of injury severity. en_US
dc.language.iso eng en_US
dc.publisher Elsevier en_US
dc.rights info:eu-repo/semantics/embargoedAccess en_US
dc.subject Predictive Analytics en_US
dc.subject Risk Factors en_US
dc.subject Machine Learning en_US
dc.subject Sensitivity Analysis en_US
dc.subject Tahmine Dayalı Analiz en_US
dc.subject Risk Faktörleri en_US
dc.subject Makine Öğrenimi en_US
dc.subject Duyarlılık Analizi en_US
dc.title Investigating injury severity risk factors in automobile crashes with predictive analytics and sensitivity analysis methods en_US
dc.type Article en_US
dc.contributor.authorID 263172 en_US
dc.contributor.authorID 110683 en_US
dc.contributor.authorID 115624 en_US
dc.relation.journal Journal of Transport&Health en_US


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