Injury severity prediction of traffic crashes with ensemble machine learning techniques: A comparative study
A better understanding of injury severity risk factors is fundamental to improving crash
prediction and effective implementation of appropriate mitigation strategies. Traditional …
prediction and effective implementation of appropriate mitigation strategies. Traditional …
Hybrid feature selection-based machine learning Classification system for the prediction of injury severity in single and multiple-vehicle accidents
To undertake a reliable analysis of injury severity in road traffic accidents, a complete
understanding of important attributes is essential. As a result of the shift from traditional …
understanding of important attributes is essential. As a result of the shift from traditional …
A literature review of machine learning algorithms for crash injury severity prediction
Introduction: Road traffic crashes represent a major public health concern, so it is of
significant importance to understand the factors associated with the increase of injury …
significant importance to understand the factors associated with the increase of injury …
Predicting crash injury severity with machine learning algorithm synergized with clustering technique: A promising protocol
Predicting crash injury severity is a crucial constituent of reducing the consequences of
traffic crashes. This study developed machine learning (ML) models to predict crash injury …
traffic crashes. This study developed machine learning (ML) models to predict crash injury …
Comparing prediction performance for crash injury severity among various machine learning and statistical methods
Crash injury severity prediction is a promising research target in traffic safety. Traditionally,
various statistical methods were used for modeling crash injury severities. In recent years …
various statistical methods were used for modeling crash injury severities. In recent years …
Predicting and analyzing road traffic injury severity using boosting-based ensemble learning models with SHAPley Additive exPlanations
Road traffic accidents are one of the world's most serious problems, as they result in
numerous fatalities and injuries, as well as economic losses each year. Assessing the …
numerous fatalities and injuries, as well as economic losses each year. Assessing the …
Predicting Freeway Traffic Crash Severity Using XGBoost‐Bayesian Network Model with Consideration of Features Interaction
Y Yang, K Wang, Z Yuan, D Liu - Journal of advanced …, 2022 - Wiley Online Library
In the field of freeway traffic safety research, there is an increasing focus in studies on how to
reduce the frequency and severity of traffic crashes. Although many studies divide factors …
reduce the frequency and severity of traffic crashes. Although many studies divide factors …
Predicting road crash severity using classifier models and crash hotspots
The rapid increase in traffic volume on urban roads, over time, has altered the global traffic
scenario. Additionally, it has increased the number of road crashes, some of which are …
scenario. Additionally, it has increased the number of road crashes, some of which are …
Using machine learning models to forecast severity level of traffic crashes by R Studio and ArcGIS
This study describes crash causes, conditions, and distribution of accident hot spots along
with an analysis of the risk factors that significantly affect severity levels of crashes and their …
with an analysis of the risk factors that significantly affect severity levels of crashes and their …
Commercial truck crash injury severity analysis using gradient boosting data mining model
Introduction Truck crashes contribute to a large number of injuries and fatalities. This study
seeks to identify the contributing factors affecting truck crash severity using 2010 to 2016 …
seeks to identify the contributing factors affecting truck crash severity using 2010 to 2016 …