Survey of accidents in suburban Tehran and the prediction of future events based on a time-series model

Journal Title: Electronic Physician - Year 2014, Vol 6, Issue 1

Abstract

Introduction: Car accidents are currently a social issue globally because they result in the deaths of many people. The aim of this study was to examine traffic accidents in suburban Tehran and forecast the number of future accidents using a time-series model. Methods: The sample population of this cross-sectional study was all traffic accidents that caused death and physical injuries in suburban Tehran in 2010 and 2011, as registered by the Tehran Emergency Section. In the present study, Minitab 15 software was used to provide a description of traffic accidents in suburban Tehran for the specified time period as well as those that occurred during April 2012. Results: The results indicated that the average number of traffic accidents in suburban Tehran per day in 2010 was 7.91 with a standard deviation of 7.70. This figure for 2011 was 6 daily traffic accidents with a standard deviation of 5.30. A one-way analysis of variance indicated that the average of traffic accidents in suburban Tehran was different for different months of the year (P = 0.000). The study results showed that different seasons in 2010 and 2011 had significantly different numbers of traffic accidents (P < 0.05). Through an auto-regressive moving average (ARMA), it was predicted that there would be 166 traffic accidents in April 2012 with a mean of 5.53 and maximum of 6 traffic accidents/day. Conclusion: There has been a decreasing trend in the average number of traffic accidents per day.

Authors and Affiliations

Ghulam Heidar Teymuri, Rahman Bahmani, Mehdi Asghari, Elham Madrese, Abdolrasoul Rahmani, Marzieh Abbasini, Iman Ahmadnezhad

Keywords

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  • EP ID EP147353
  • DOI -
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How To Cite

Ghulam Heidar Teymuri, Rahman Bahmani, Mehdi Asghari, Elham Madrese, Abdolrasoul Rahmani, Marzieh Abbasini, Iman Ahmadnezhad (2014). Survey of accidents in suburban Tehran and the prediction of future events based on a time-series model. Electronic Physician, 6(1), 754-758. https://europub.co.uk/articles/-A-147353