Using Artificial Neural Network to Destroy the Process of Traffic Accident Victims in Yazd Province

Background: Road accidents are among the most important causes of death and severe personal and financial injuries. Also, its profound social, cultural, and economic effects threaten human societies. This study aimed to estimate the trend of traffic accident victims in Yazd Province, Iran, to predict the number of traffic accident victims in this province. Materials and Methods: Based on traffic casualty statistics referred to forensic medicine in Yazd Province within April ۱۹۸۹ and March ۲۰۱۷ referred to Forensic Medicine of Yazd Province and using an artificial neural network to predict the number of injured for ۱۲ months ending in ۲۰۲۰ has been paid. The neural network used in this study had ۱۲ inputs, one output, and ۵ hidden layers. The network predicts the relationship between data after training and learning. The network is considered the MSE benchmark. Results: The number of injured in traffic accidents in Yazd Province in ۲۰۲۰ was equal to ۷۰۵۲ people, with the highest number in December with ۸۳۲ people and the lowest in June with ۴۱۴ people. The exact method of use was equal to ۹۲ cases. Conclusion: The trend of traffic accident casualties in Yazd Province in ۲۰۲۰ will be declining. For future research, the exact method designed in this study can be examined with other methods for the best response level.

Keywords:

Crash , Trauma , Accidents