activity
20202022
most citedShort-term passenger flow prediction for multi-traffic modes: A Transformer and residual network based multi-task learning method

4 citations · 5 across the 4 of their papers we have counts for

collaborators

6 papers

cs.LG2022

Meta-learning Based Short-Term Passenger Flow Prediction for Newly-Operated Urban Rail Transit Stations

Kuo Han, Jinlei Zhang, Chunqi Zhu +3

Accurate short-term passenger flow prediction in urban rail transit stations has great benefits for reasonably allocating resources, easing congestion, and reducing operational ris…

cs.LG20224 cited

Short-term passenger flow prediction for multi-traffic modes: A Transformer and residual network based multi-task learning method

Yongjie Yang, Jinlei Zhang, Lixing Yang +2

With the prevailing of mobility as a service (MaaS), it becomes increasingly important to manage multi-traffic modes simultaneously and cooperatively. As an important component of…

cs.LG2022

An end-to-end predict-then-optimize clustering method for intelligent assignment problems in express systems

Jinlei Zhang, Ergang Shan, Lixia Wu +3

Express systems play important roles in modern major cities. Couriers serving for the express system pick up packages in certain areas of interest (AOI) during a specific time. How…

cs.LG20211 cited

Network-wide link travel time and station waiting time estimation using automatic fare collection data: A computational graph approach

Jinlei Zhang, Feng Chen, Lixing Yang +3

Urban rail transit (URT) system plays a dominating role in many megacities like Beijing and Hong Kong. Due to its important role and complex nature, it is always in great need for…

eess.SP2020

Short-term origin-destination demand prediction in urban rail transit systems: A channel-wise attentive split-convolutional neural network method

Jinlei Zhang, Hongshu Che, Feng Chen +2

Short-term origin-destination (OD) flow prediction in urban rail transit (URT) plays a crucial role in smart and real-time URT operation and management. Different from other short-…

physics.soc-ph2020

Multi-graph convolutional network for short-term passenger flow forecasting in urban rail transit

Jinlei Zhang, Feng Chen, Yinan Guo +1

Short-term passenger flow forecasting is a crucial task for urban rail transit operations. Emerging deep-learning technologies have become effective methods used to overcome this p…