Identify Risk Pattern of E-Bike Riders in China Based on Machine Learning Framework

Predicting Future Driving Risk of Crash-Involved Drivers Based on a Systematic Machine Learning Framework

(2019) Chen Wang et al.   International Journal of Environmental Research and Public Health

A Comprehensive Analysis of Synthetic Minority Oversampling Technique (SMOTE) for handling class imbalance

(2019) Dina Elreedy et al.   INFORMATION SCIENCES

Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo

(2018) Chuan Ding et al.   TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE

A combined use of microscopic traffic simulation and extreme value methods for traffic safety evaluation

(2018) Chen Wang et al.   TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES

Evaluation of Factors Affecting E-Bike Involved Crash and E-Bike License Plate Use in China Using a Bivariate Probit Model

(2017) Yanyong Guo et al.   JOURNAL OF ADVANCED TRANSPORTATION

Modeling faults among e-bike-related fatal crashes in China

(2016) Chen Wang et al.   Traffic Injury Prevention

Evaluating bicycle–vehicle conflicts and delays on urban streets with bike lane and on-street parking

(2016) Jingxu Chen et al.   Transportation Letters-The International Journal of Transportation Research

Related Risk Factors for Injury Severity of E-bike and Bicycle Crashes in Hefei

(2013) Feng Hu et al.   Traffic Injury Prevention

Traffic Safety for Electric Bike Riders in China

(2013) Lin Yao et al.   TRANSPORTATION RESEARCH RECORD

E-bikes and urban transportation: emerging issues and unresolved questions

(2011) Geoffrey Rose   TRANSPORTATION

Electric-bicycle-related injury: a rising traffic injury burden in China

(2010) Z. Feng et al.   INJURY PREVENTION

AdaBoost-Based Algorithm for Network Intrusion Detection

(2008) Weiming Hu et al.   IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS