Mining relationships among knowledge, attitude, and practice of drivers using self-organizing map and decision tree: The case of Bandar Abbas city taxi drivers
Background and Objectives: Traffic accidents are the leading causes of fatal or nonfatal work-related injuries in many countries. Analyzing influencing factors on knowledge, attitude, and practice of drivers is a topic of interest for policymakers to decrease traffic accident injury victims. Materia...
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Format: | Article |
Language: | English |
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Kashan University of Medical Sciences
2018-01-01
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Series: | Archives of Trauma Research |
Subjects: | |
Online Access: | http://www.archtrauma.com/article.asp?issn=2251-953X;year=2018;volume=7;issue=2;spage=73;epage=79;aulast=Hadavandi |
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author | Esmaeil Hadavandi Leila Omidi Abdolhamid Tajvar Ali Ghanbari |
author_facet | Esmaeil Hadavandi Leila Omidi Abdolhamid Tajvar Ali Ghanbari |
author_sort | Esmaeil Hadavandi |
collection | DOAJ |
description | Background and Objectives: Traffic accidents are the leading causes of fatal or nonfatal work-related injuries in many countries. Analyzing influencing factors on knowledge, attitude, and practice of drivers is a topic of interest for policymakers to decrease traffic accident injury victims. Materials and Methods: In this article, a two-stage data mining approach was presented for determining the mining relationships among knowledge, attitude, and practice of drivers. In the first stage, because of existing multidimensional practice variables, self-organizing map neural network was utilized to automatically arrange drivers into two safe and unsafe driving practice clusters. In the second stage, a decision tree was used to model relationships among knowledge and attitude of drivers and practice clusters. The authors' designed questionnaires were used to collect data in 235 male taxi drivers of Bandar Abbas city in Iran regarding the drivers' knowledge and attitude toward traffic regulations. The driving practices were assessed using a prepared checklist. Results: The most important attribute affecting practice of drivers was the maximum safe speed in the city. Conclusions: The results of this investigation showed that drivers' knowledge toward traffic regulations had a dramatic impact on safe driving practices. Levels of drivers' education can influence practice of drivers. |
first_indexed | 2024-03-12T11:20:32Z |
format | Article |
id | doaj.art-3dd5d08027ca4f8692058a5346cce663 |
institution | Directory Open Access Journal |
issn | 2251-953X |
language | English |
last_indexed | 2024-03-12T11:20:32Z |
publishDate | 2018-01-01 |
publisher | Kashan University of Medical Sciences |
record_format | Article |
series | Archives of Trauma Research |
spelling | doaj.art-3dd5d08027ca4f8692058a5346cce6632023-09-02T00:16:57ZengKashan University of Medical SciencesArchives of Trauma Research2251-953X2018-01-0172737910.4103/atr.atr_30_18Mining relationships among knowledge, attitude, and practice of drivers using self-organizing map and decision tree: The case of Bandar Abbas city taxi driversEsmaeil HadavandiLeila OmidiAbdolhamid TajvarAli GhanbariBackground and Objectives: Traffic accidents are the leading causes of fatal or nonfatal work-related injuries in many countries. Analyzing influencing factors on knowledge, attitude, and practice of drivers is a topic of interest for policymakers to decrease traffic accident injury victims. Materials and Methods: In this article, a two-stage data mining approach was presented for determining the mining relationships among knowledge, attitude, and practice of drivers. In the first stage, because of existing multidimensional practice variables, self-organizing map neural network was utilized to automatically arrange drivers into two safe and unsafe driving practice clusters. In the second stage, a decision tree was used to model relationships among knowledge and attitude of drivers and practice clusters. The authors' designed questionnaires were used to collect data in 235 male taxi drivers of Bandar Abbas city in Iran regarding the drivers' knowledge and attitude toward traffic regulations. The driving practices were assessed using a prepared checklist. Results: The most important attribute affecting practice of drivers was the maximum safe speed in the city. Conclusions: The results of this investigation showed that drivers' knowledge toward traffic regulations had a dramatic impact on safe driving practices. Levels of drivers' education can influence practice of drivers.http://www.archtrauma.com/article.asp?issn=2251-953X;year=2018;volume=7;issue=2;spage=73;epage=79;aulast=Hadavandiattitudedecision treedriversknowledgepracticeself-organizing map |
spellingShingle | Esmaeil Hadavandi Leila Omidi Abdolhamid Tajvar Ali Ghanbari Mining relationships among knowledge, attitude, and practice of drivers using self-organizing map and decision tree: The case of Bandar Abbas city taxi drivers Archives of Trauma Research attitude decision tree drivers knowledge practice self-organizing map |
title | Mining relationships among knowledge, attitude, and practice of drivers using self-organizing map and decision tree: The case of Bandar Abbas city taxi drivers |
title_full | Mining relationships among knowledge, attitude, and practice of drivers using self-organizing map and decision tree: The case of Bandar Abbas city taxi drivers |
title_fullStr | Mining relationships among knowledge, attitude, and practice of drivers using self-organizing map and decision tree: The case of Bandar Abbas city taxi drivers |
title_full_unstemmed | Mining relationships among knowledge, attitude, and practice of drivers using self-organizing map and decision tree: The case of Bandar Abbas city taxi drivers |
title_short | Mining relationships among knowledge, attitude, and practice of drivers using self-organizing map and decision tree: The case of Bandar Abbas city taxi drivers |
title_sort | mining relationships among knowledge attitude and practice of drivers using self organizing map and decision tree the case of bandar abbas city taxi drivers |
topic | attitude decision tree drivers knowledge practice self-organizing map |
url | http://www.archtrauma.com/article.asp?issn=2251-953X;year=2018;volume=7;issue=2;spage=73;epage=79;aulast=Hadavandi |
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