TY  - JOUR
PY  - 2023//
TI  - Analysis of the severity of accidents on rural roads using statistical and artificial neural network methods
JO  - Journal of advanced transportation
A1  - Habibzadeh, Mohammad
A1  - Ayar, Pooyan
A1  - Mirabimoghaddam, Mohammad Hassan
A1  - Ameri, Mahmoud
A1  - Sadat Haghighi, Seyede Mojde
SP  - e8089395
EP  - e8089395
VL  - 2023
IS  - 
N2  - 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.<p />  <p>Language: en</p>
LA  - en
SN  - 0197-6729
UR  - http://dx.doi.org/10.1155/2023/8089395
ID  - ref1
ER  -