Motorcyclist injury severity analysis: a comparison of Artificial Neural Networks and random parameter model with heterogeneity in means and variances

Investigation of factors influencing motorcyclist injury severity using random parameters logit model with heterogeneity in means and variances

(2021) Muhammad Ijaz et al.   INTERNATIONAL JOURNAL OF CRASHWORTHINESS

The effect of motorcyclists’ age on injury severities in single-motorcycle crashes with unobserved heterogeneity

(2021) Mouyid Islam   JOURNAL OF SAFETY RESEARCH

Injury severity analysis of motorcycle crashes: A comparison of latent class clustering and latent segmentation based models with unobserved heterogeneity

(2021) Fangrong Chang et al.   Analytic Methods in Accident Research

Temporal analysis of crash severities involving male and female drivers: A random parameters approach with heterogeneity in means and variances

(2021) Xintong Yan et al.   Analytic Methods in Accident Research

Fusion convolutional neural network-based interpretation of unobserved heterogeneous factors in driver injury severity outcomes in single-vehicle crashes

(2021) Hao Yu et al.   Analytic Methods in Accident Research

Empirical comparison of the effects of urban and rural crashes on motorcyclist injury severities: A correlated random parameters ordered probit approach with heterogeneity in means

(2021) Chamroeun Se et al.   ACCIDENT ANALYSIS AND PREVENTION

Factors affecting motorcycle crash casualty severity at signalized and non-signalized intersections in Ghana: Insights from a data mining and binary logit regression approach

(2021) Reuben Tamakloe et al.   ACCIDENT ANALYSIS AND PREVENTION

Temporal stability of factors influencing driver-injury severities in single-vehicle crashes: A correlated random parameters with heterogeneity in means and variances approach

(2021) Chamroeun Se et al.   Analytic Methods in Accident Research

Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network

(2020) Arshad Jamal et al.   International Journal of Environmental Research and Public Health

Motor vehicle driver injury severity analysis utilizing a random parameter binary probit model considering different types of driving licenses in 4-legs roundabouts in South Australia

(2020) Hamsa Abbas Zubaidi et al.   SAFETY SCIENCE

Examination of driver injury severity in freeway single-vehicle crashes using a mixed logit model with heterogeneity-in-means

(2019) Qinzhong Hou et al.   PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS

Modeling Safety Effects of Horizontal Curve Design on Injury Severity of Single-Motorcycle Crashes with Mixed-Effects Logistic Model

(2017) Chunfu Xin et al.   TRANSPORTATION RESEARCH RECORD

Safety impacts of pavement surface roughness at two-lane and multi-lane highways: accounting for heterogeneity and seemingly unrelated correlation across crash severities

(2017) Sikai Chen et al.   Transportmetrica A-Transport Science

Estimation of Routine Maintenance Expenditures for Highway Pavement Segments: Accounting for Heterogeneity Using Random-Effects Models

(2017) Matthew Volovski et al.   Journal of Transportation Engineering Part A-Systems

Injury Severity of Motorcycle Riders Involved in Traffic Crashes in Hunan, China: A Mixed Ordered Logit Approach

(2016) Fangrong Chang et al.   International Journal of Environmental Research and Public Health

Risk Factors in Motorcyclist Fatalities in Taiwan

(2012) Rong-Chang Jou et al.   Traffic Injury Prevention

Comparison of Severity of Motorcyclist Injury by Crash Types

(2012) William H. Schneider et al.   TRANSPORTATION RESEARCH RECORD

A systematic analysis of performance measures for classification tasks

(2009) Marina Sokolova et al.   INFORMATION PROCESSING & MANAGEMENT

Motorcyclist injury severity in angle crashes at T-junctions: Identifying significant factors and analysing what made motorists fail to yield to motorcycles

(2009) Chih-Wei Pai   SAFETY SCIENCE

Helmet Use and Effectiveness in Reducing the Severity of Head Injuries in Thailand

(2008) Kunnawee Kanitpong et al.   TRANSPORTATION RESEARCH RECORD