Model Evaluation for Forecasting Traffic Accident Severity in Rainy Seasons Using Machine Learning Algorithms: Seoul City Study

Model Evaluation for Forecasting Traffic Accident Severity in Rainy Seasons Using Machine Learning Algorithms: Seoul City Study

There have been numerous studies on traffic accidents and their severity, particularly in relation to weather conditions and road geometry. In these studies, traditional statistical methods have been employed, such as linear regression, logistic regression, and negative binomial regression modeling,...

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Bibliographic Details
Main Authors: Jonghak Lee, Taekwan Yoon, Sangil Kwon, Jongtae Lee
Format: Article
Language:English
Published: MDPI AG 2019-12-01
Series:Applied Sciences
Subjects:
machine learning architecture
random forest model
artificial neural network
decision tree algorithm
accident severity level
road surface condition
road hazard zone forecasting
Online Access:https://www.mdpi.com/2076-3417/10/1/129

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https://www.mdpi.com/2076-3417/10/1/129

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