A Novel Framework to Use Association Rule Mining for classification of traffic accident severity

Introduction: Traffic accidents are an undesirable burden on society. Every year around one million deaths and more than ten million injuries are reported due to traffic accidents. Hence, traffic accidents prevention measures must be taken to overcome the accident rate. Different countries have diff...

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Autores:
Gupta, Meenu
Kumar Solanki, Vijender
Kumar Singh, Vijay
Tipo de recurso:
Article of journal
Fecha de publicación:
2017
Institución:
Universidad Cooperativa de Colombia
Repositorio:
Repositorio UCC
Idioma:
eng
OAI Identifier:
oai:repository.ucc.edu.co:20.500.12494/9403
Acceso en línea:
https://revistas.ucc.edu.co/index.php/in/article/view/1726
https://hdl.handle.net/20.500.12494/9403
Palabra clave:
Rights
openAccess
License
Copyright (c) 2017 Journal of Engineering and Education
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oai_identifier_str oai:repository.ucc.edu.co:20.500.12494/9403
network_acronym_str COOPER2
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repository_id_str
spelling Gupta, MeenuKumar Solanki, VijenderKumar Singh, Vijay2017-01-012019-05-14T21:07:52Z2019-05-14T21:07:52Zhttps://revistas.ucc.edu.co/index.php/in/article/view/172610.16925/in.v13i21.1726https://hdl.handle.net/20.500.12494/9403Introduction: Traffic accidents are an undesirable burden on society. Every year around one million deaths and more than ten million injuries are reported due to traffic accidents. Hence, traffic accidents prevention measures must be taken to overcome the accident rate. Different countries have different geographical and environmental conditions and hence the accident factors diverge in each country. Traffic accident data analysis is very useful in revealing the factors that affect the accidents in different countries. This article was written in the year 2016 in the Institute of Technology & Science, Mohan Nagar, Ghaziabad, up, India. Methology: We propose a framework to utilize association rule mining (arm) for the severity classification of traffic accidents data obtained from police records in Mujjafarnagar district, Uttarpradesh, India. Results: The results certainly reveal some hidden factors which can be applied to understand the factors behind road accidentality in this region. Conclusions: The framework enables us to find three clusters from the data set. Each cluster represents a type of accident severity, i.e. fatal, major injury and minor/no injury. The association rules exposed different factors that are associated with road accidents in each category. The information extracted provides important information which can be employed to adapt preventive measures to overcome the accident severity in Muzzafarnagar district.application/pdfengUniversidad Cooperativa de Colombiahttps://revistas.ucc.edu.co/index.php/in/article/view/1726/1844https://revistas.ucc.edu.co/index.php/in/article/view/1726/2487Copyright (c) 2017 Journal of Engineering and Educationhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Ingeniería Solidaria; Vol 13 No 21 (2017); 37-44Ingeniería Solidaria; Vol. 13 Núm. 21 (2017); 37-44Ingeniería Solidaria; v. 13 n. 21 (2017); 37-442357-60141900-3102A Novel Framework to Use Association Rule Mining for classification of traffic accident severityArtículohttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articlehttp://purl.org/redcol/resource_type/ARTinfo:eu-repo/semantics/publishedVersionPublication20.500.12494/9403oai:repository.ucc.edu.co:20.500.12494/94032024-07-16 13:30:30.254metadata.onlyhttps://repository.ucc.edu.coRepositorio Institucional Universidad Cooperativa de Colombiabdigital@metabiblioteca.com
dc.title.eng.fl_str_mv A Novel Framework to Use Association Rule Mining for classification of traffic accident severity
title A Novel Framework to Use Association Rule Mining for classification of traffic accident severity
spellingShingle A Novel Framework to Use Association Rule Mining for classification of traffic accident severity
title_short A Novel Framework to Use Association Rule Mining for classification of traffic accident severity
title_full A Novel Framework to Use Association Rule Mining for classification of traffic accident severity
title_fullStr A Novel Framework to Use Association Rule Mining for classification of traffic accident severity
title_full_unstemmed A Novel Framework to Use Association Rule Mining for classification of traffic accident severity
title_sort A Novel Framework to Use Association Rule Mining for classification of traffic accident severity
dc.creator.fl_str_mv Gupta, Meenu
Kumar Solanki, Vijender
Kumar Singh, Vijay
dc.contributor.author.none.fl_str_mv Gupta, Meenu
Kumar Solanki, Vijender
Kumar Singh, Vijay
description Introduction: Traffic accidents are an undesirable burden on society. Every year around one million deaths and more than ten million injuries are reported due to traffic accidents. Hence, traffic accidents prevention measures must be taken to overcome the accident rate. Different countries have different geographical and environmental conditions and hence the accident factors diverge in each country. Traffic accident data analysis is very useful in revealing the factors that affect the accidents in different countries. This article was written in the year 2016 in the Institute of Technology & Science, Mohan Nagar, Ghaziabad, up, India. Methology: We propose a framework to utilize association rule mining (arm) for the severity classification of traffic accidents data obtained from police records in Mujjafarnagar district, Uttarpradesh, India. Results: The results certainly reveal some hidden factors which can be applied to understand the factors behind road accidentality in this region. Conclusions: The framework enables us to find three clusters from the data set. Each cluster represents a type of accident severity, i.e. fatal, major injury and minor/no injury. The association rules exposed different factors that are associated with road accidents in each category. The information extracted provides important information which can be employed to adapt preventive measures to overcome the accident severity in Muzzafarnagar district.
publishDate 2017
dc.date.accessioned.none.fl_str_mv 2019-05-14T21:07:52Z
dc.date.available.none.fl_str_mv 2019-05-14T21:07:52Z
dc.date.none.fl_str_mv 2017-01-01
dc.type.none.fl_str_mv Artículo
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.coar.none.fl_str_mv http://purl.org/coar/resource_type/c_6501
dc.type.coarversion.none.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.driver.none.fl_str_mv info:eu-repo/semantics/article
dc.type.redcol.none.fl_str_mv http://purl.org/redcol/resource_type/ART
dc.type.version.none.fl_str_mv info:eu-repo/semantics/publishedVersion
format http://purl.org/coar/resource_type/c_6501
status_str publishedVersion
dc.identifier.none.fl_str_mv https://revistas.ucc.edu.co/index.php/in/article/view/1726
10.16925/in.v13i21.1726
dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12494/9403
url https://revistas.ucc.edu.co/index.php/in/article/view/1726
https://hdl.handle.net/20.500.12494/9403
identifier_str_mv 10.16925/in.v13i21.1726
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://revistas.ucc.edu.co/index.php/in/article/view/1726/1844
https://revistas.ucc.edu.co/index.php/in/article/view/1726/2487
dc.rights.none.fl_str_mv Copyright (c) 2017 Journal of Engineering and Education
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessrights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.coar.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Copyright (c) 2017 Journal of Engineering and Education
http://creativecommons.org/licenses/by-nc-nd/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.eng.fl_str_mv Universidad Cooperativa de Colombia
dc.source.eng.fl_str_mv Ingeniería Solidaria; Vol 13 No 21 (2017); 37-44
dc.source.spa.fl_str_mv Ingeniería Solidaria; Vol. 13 Núm. 21 (2017); 37-44
dc.source.por.fl_str_mv Ingeniería Solidaria; v. 13 n. 21 (2017); 37-44
dc.source.none.fl_str_mv 2357-6014
1900-3102
institution Universidad Cooperativa de Colombia
repository.name.fl_str_mv Repositorio Institucional Universidad Cooperativa de Colombia
repository.mail.fl_str_mv bdigital@metabiblioteca.com
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