Advanced

Incident management in urban transportation: application of data mining

Zegordi, S. Hessamedin; Aghdasi, Mohammad; Davarzani, Hoda LU and Gh. Tehrani, Nasim (2010) In SCIT Journal 10(1). p.19-28
Abstract
Better understanding of the impacts of an incident may help analysts to design more appropriate incident management strategies. Very little is known to date about the usefulness of applying data mining in traffic and transport related research, although data mining has contributed its usefulness significantly in other fields. This research is intended to discover the relationship between motor vehicle accidents and the comprehensive information about people, vehicles, and conditions recorded in Police Accident Reports using data mining techniques. The data obtained from the traffic police's accident database, are first clustered using the K-mean method. Then, by exploring the extracted patterns and rules, some refinements in behaviors are... (More)
Better understanding of the impacts of an incident may help analysts to design more appropriate incident management strategies. Very little is known to date about the usefulness of applying data mining in traffic and transport related research, although data mining has contributed its usefulness significantly in other fields. This research is intended to discover the relationship between motor vehicle accidents and the comprehensive information about people, vehicles, and conditions recorded in Police Accident Reports using data mining techniques. The data obtained from the traffic police's accident database, are first clustered using the K-mean method. Then, by exploring the extracted patterns and rules, some refinements in behaviors are proposed. So by using this innovative method, regardless of the constraints of this study, useful knowledge about the enhancement of safety of driving and roads and managing the accidents are provided. (Less)
Please use this url to cite or link to this publication:
author
publishing date
type
Contribution to journal
publication status
published
subject
in
SCIT Journal
volume
10
issue
1
pages
19 - 28
ISSN
0974-5076
language
English
LU publication?
no
id
e9846114-2639-4525-9e1d-4870b4176e4a (old id 3404846)
date added to LUP
2013-01-22 14:41:45
date last changed
2016-06-29 08:55:47
@misc{e9846114-2639-4525-9e1d-4870b4176e4a,
  abstract     = {Better understanding of the impacts of an incident may help analysts to design more appropriate incident management strategies. Very little is known to date about the usefulness of applying data mining in traffic and transport related research, although data mining has contributed its usefulness significantly in other fields. This research is intended to discover the relationship between motor vehicle accidents and the comprehensive information about people, vehicles, and conditions recorded in Police Accident Reports using data mining techniques. The data obtained from the traffic police's accident database, are first clustered using the K-mean method. Then, by exploring the extracted patterns and rules, some refinements in behaviors are proposed. So by using this innovative method, regardless of the constraints of this study, useful knowledge about the enhancement of safety of driving and roads and managing the accidents are provided.},
  author       = {Zegordi, S. Hessamedin and Aghdasi, Mohammad and Davarzani, Hoda and Gh. Tehrani, Nasim},
  issn         = {0974-5076},
  language     = {eng},
  number       = {1},
  pages        = {19--28},
  series       = {SCIT Journal},
  title        = {Incident management in urban transportation: application of data mining},
  volume       = {10},
  year         = {2010},
}