首页|Analysis of the Severity of Accidents on Rural Roads Using Statistical and Artificial Neural Network Methods
Analysis of the Severity of Accidents on Rural Roads Using Statistical and Artificial Neural Network Methods
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NETL
NSTL
Wiley-Hindawi
This study assesses the relationship that existed between various variables and their subvariables on rural roads in Qom, Iran, using statistical analysis and calculates the relationship between the considered factors and accident severity. A logit model was applied to determine the factors affecting the severity of accidents. In addition, two artificial neural network (ANN) models were developed using two kinds of learning methods to train neurons to select the best result. The results of modeling and analysis of accidents using various techniques revealed that each technique, depending on its purpose, examined the severity of accidents from a different point of view and represented various outcomes. Finally, the performance of the proposed models was validated utilizing other mathematical models. As a result, putting the output results together, the best measures can be suggested to increase the safety of people on rural roads. The outcomes of this study may aid these service providers in strategic planning and policy framework.
Mohammad Habibzadeh、Pooyan Ayar、Mohammad Hassan Mirabimoghaddam、Mahmoud Ameri、Seyede Mojde Sadat Haghighi、Yajie Zou
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School of Civil Engineering Iran University of Science & Technology (IUST) Tehran
Department of Civil Engineering University of Sistan and Baluchestan Zahedan
NETL
NSTL
Wiley-Hindawi
