A Hybrid Method for Traffic Incident Detection Using Random Forest-Recursive Feature Elimination and Long Short-Term Memory Network With Bayesian Optimization Algorithm. - Qiang Shang; Linlin Feng; Song Gao (IEEE Access, 2021)

Correction to "A Hybrid Method for Traffic Incident Detection Using Random Forest-Recursive Feature Elimination and Long Short-Term Memory Network With Bayesian Optimization Algorithm". - Qiang Shang; Linlin Feng; Song Gao (IEEE Access, 2021)

A Hybrid Model for Short-Term Traffic Flow Prediction Based on Variational Mode Decomposition, Wavelet Threshold Denoising, and Long Short-Term Memory Neural Network. - Yang Yu 072; Qiang Shang; Tian Xie 010 (Complex., 2021)

Automated Traffic Incident Detection: Coping With Imbalanced and Small Datasets. - Tian Xie 010; Qiang Shang; Yang Yu 072 (IEEE Access, 2022)

A Distracted Driving Detection Model Based On Driving Performance. - Bingxu Fu; Qiang Shang; Teng Sun; Shuo Jia (IEEE Access, 2023)

A Novel Hybrid Model for Short-Term Traffic Flow Prediction Based on Spatio-Temporal Deep Learning With Considering Associated Factors Selection. - Yingping Tang; Qiang Shang; Longjiao Yin (IEEE Access, 2024)

Traffic congestion recognition based on convolutional neural networks in different scenarios. - Chao Wang; Qiang Shang; Kun Liu; Wenxue Zhang (Eng. Appl. Artif. Intell., 2025)

Traffic Flow Prediction Framework That Can Appropriately Process the Noise, Volatility, and Nonlinearity in Traffic Flow Data. - Yingping Tang; Qiang Shang; Longjiao Yin; Hu Zhang (Int. J. Intell. Syst., 2025)