Research on Sample Selection of Urban Rail Transit Passenger Flow Forecasting Based on SCBP Algorithm. - Wenbo Lu; Chaoqun Ma; Peikun Li (IEEE Access, 2020)

Mul-DesLSTM: An integrative multi-time granularity deep learning prediction method for urban rail transit short-term passenger flow. - Wenbo Lu; Yong Zhang; Peikun Li; Ting Wang (Eng. Appl. Artif. Intell., 2023)

MOHP-EC: A Multiobjective Hierarchical Prediction Framework for Urban Rail Transit Passenger Flow. - Wenbo Lu; Jinhua Xu; Yong Zhang 011; Ting Wang; Peikun Li (IEEE Intell. Transp. Syst. Mag., 2023)

Estimating urban rail transit passenger inflow caused by special events occurrences fusing multi-source data. - Wenbo Lu; Yong Zhang 011; Peikun Li; Ting Wang (Neural Comput. Appl., 2023)

METcross: A framework for short-term forecasting of cross-city metro passenger flow. - Wenbo Lu; Jinhua Xu; Peikun Li; Ting Wang; Yong Zhang 011 (CoRR, 2024)

IPF-HMGNN: A novel integrative prediction framework for metro passenger flow. - Wenbo Lu; Yong Zhang; Hai L. Vu; Jinhua Xu; Peikun Li (CoRR, 2024)