Junhua Wang
- Risk analysis of bridge maintenance accidents: A two-stage LEC method and Bayesian network approach. Dans: International Journal of Transportation Science and Technology. :
- Risk prediction for cut-ins using multi-driver simulation data and machine learning algorithms: A comparison among decision tree, GBDT and LSTM. Dans: International Journal of Transportation Science and Technology, v. 12, n. 3 (septembre 2023). (2023):
- Cyclic behavior of self-slitting squat composite shear walls with concrete-filled steel tubes: Experiment. Dans: Journal of Constructional Steel Research, v. 210 (novembre 2023). (2023):
- TBM performance prediction using LSTM-based hybrid neural network model: Case study of Baimang River tunnel project in Shenzhen, China. Dans: Underground Space, v. 11 (août 2023). (2023):
- Crash prediction for freeway work zones in real time: A comparison between Convolutional Neural Network and Binary Logistic Regression model. Dans: International Journal of Transportation Science and Technology, v. 11, n. 3 (septembre 2022). (2022):
- Realtime wide-area vehicle trajectory tracking using millimeter-wave radar sensors and the open TJRD TS dataset. Dans: International Journal of Transportation Science and Technology, v. 12, n. 1 (mars 2023). (2023):
- Seismic behaviors and resilient capacity of CFRP-confined concrete columns with partially debonded high-strength steel rebars. Dans: Composite Structures, v. 222 (août 2019). (2019):
- Influence of Bond Property of Longitudinal Bars on Seismic Behaviors of RC Columns. Dans: Magazine of Concrete Research, v. 72, n. 15 (août 2020). (2020):
- An Equivalent Stress Block for Characterizing Force–Displacement Behavior of Circular RC Column Considering Steel Bond Slip. Dans: Magazine of Concrete Research, v. 72, n. 22 (novembre 2020). (2020):
- (2015): Mechanical Properties and Evaluation of Concrete Beams Made of a Large Amount of Fine Fly Ash. Présenté pendant: IABSE Conference: Elegance in structures, Nara, Japan, 13-15 May 2015.
- (2017): Real-time crash prediction on freeways using data mining and emerging techniques. Dans: Journal of Modern Transportation, v. 25, n. 2 (juin 2017).