Mahdi Rezapour
- Editorial: Data science methods for solving real-world problems in transportation, security and beyond. Dans: Frontiers in Built Environment, v. 10 (février 2024). (2024):
- (2022): Random regret minimization for analyzing driver actions, accounting for preference heterogeneity. Dans: Frontiers in Built Environment, v. 8 (février 2022).
- (2022): Hybrid random utility-random regret model in the presence of preference heterogeneity, modeling drivers’ actions. Dans: Frontiers in Built Environment, v. 8 (février 2022).
- An investigation of influential factors of downgrade truck crashes: A logistic regression approach. Dans: Journal of Traffic and Transportation Engineering (English Edition), v. 6, n. 2 (avril 2019). (2019):
- Predicting injury severity and crash frequency: Insights into the impacts of geometric variables on downgrade crashes in Wyoming. Dans: Journal of Traffic and Transportation Engineering (English Edition), v. 7, n. 3 (juin 2020). (2020):
- Investigating the relationship between crash severity, traffic barrier type, and vehicle type in crashes involving traffic barrier. Dans: Journal of Traffic and Transportation Engineering (English Edition), v. 7, n. 1 (février 2020). (2020):
- Analyzing injury severity of motorcycle at-fault crashes using machine learning techniques, decision tree and logistic regression models. Dans: International Journal of Transportation Science and Technology, v. 9, n. 2 (juin 2020). (2020):
- (2019): Modeling traffic barriers crash severity by considering the effect of traffic barrier dimensions. Dans: Journal of Modern Transportation, v. 27, n. 2 (avril 2019).
- (2018): Application of multinomial and ordinal logistic regression to model injury severity of truck crashes, using violation and crash data. Dans: Journal of Modern Transportation, v. 26, n. 4 (novembre 2018).