dc.contributor.author | Sinclair, C | |
dc.contributor.author | Das, S | |
dc.date.accessioned | 2021-03-17T15:02:50Z | |
dc.date.issued | 2021-03-16 | |
dc.description.abstract | The goal of this paper is to use the unsupervised
machine learning method in road accident analytics, especially
using k-means clustering to identify patterns and understand
the relationships between variables recorded by the UK police
department. These include features like number of casualties,
number of vehicles, age of vehicle and age bracket of the driver.
We aim to describe clusters of accidents based on similarity
measures in the features and identify what separates each one. | en_GB |
dc.description.sponsorship | Engineering and Physical Sciences Research Council (EPSRC) | en_GB |
dc.identifier.citation | 2021 International Conference on Sustainable Energy and Future Electric Transportation (SEFET), 21 - 23 January 2021, Hyderabad, India | en_GB |
dc.identifier.doi | 10.1109/sefet48154.2021.9375817 | |
dc.identifier.uri | http://hdl.handle.net/10871/125145 | |
dc.language.iso | en | en_GB |
dc.publisher | Institute of Electrical and Electronics Engineers (IEEE) | en_GB |
dc.rights | Copyright © 2021, IEEE | en_GB |
dc.subject | clustering | en_GB |
dc.subject | road accident | en_GB |
dc.subject | geospatial analytics | en_GB |
dc.title | Traffic accidents analytics in UK urban areas using k-means clustering for geospatial mapping | en_GB |
dc.type | Conference paper | en_GB |
dc.date.available | 2021-03-17T15:02:50Z | |
dc.identifier.isbn | 978-1-7281-5681-1 | |
dc.description | This is the author accepted manuscript. The final version is available from IEEE via the DOI in this record | en_GB |
dc.rights.uri | http://www.rioxx.net/licenses/all-rights-reserved | en_GB |
rioxxterms.version | AM | en_GB |
rioxxterms.licenseref.startdate | 2021-03-16 | |
rioxxterms.type | Conference Paper/Proceeding/Abstract | en_GB |
refterms.dateFCD | 2021-03-17T13:35:46Z | |
refterms.versionFCD | AM | |
refterms.dateFOA | 2021-03-17T15:02:58Z | |
refterms.panel | B | en_GB |