Z
Zhiyuan Liu
Researcher at Southeast University
Publications - 246
Citations - 5426
Zhiyuan Liu is an academic researcher from Southeast University. The author has contributed to research in topics: Computer science & Congestion pricing. The author has an hindex of 33, co-authored 215 publications receiving 3492 citations. Previous affiliations of Zhiyuan Liu include Monash University, Clayton campus & East China Normal University.
Papers
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Bus stop-skipping scheme with random travel time
TL;DR: In this paper, a genetic algorithm incorporating Monte Carlo simulation is proposed to solve the problem of deadheading in a special case of the stop-skipping problem, allowing a bus vehicle to skip stops between the dispatching terminal point and a designated stop.
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DeepPF: A deep learning based architecture for metro passenger flow prediction
Yang Liu,Zhiyuan Liu,Ruo Jia +2 more
TL;DR: An end-to-end deep learning architecture, termed as Deep Passenger Flow (DeepPF), to forecast the metro inbound/outbound passenger flow, which achieves a high prediction accuracy due to the ease of integrating multi-source data.
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An effective spatial-temporal attention based neural network for traffic flow prediction
TL;DR: A deep learning based traffic flow predictor with spatial and temporal attentions (STANN) is proposed, which is demonstrated to have potential for improving the understanding of spatial-temporal correlations in a traffic network.
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Performance of transportation network under perturbations: Reliability, vulnerability, and resilience
TL;DR: Three representative concepts relating to network performance are covered: reliability, vulnerability, and resilience and their rationale in reflecting network performance under perturbations, yet their outputs differ.
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Electric vehicle fleet size and trip pricing for one-way carsharing services considering vehicle relocation and personnel assignment
Min Xu,Qiang Meng,Zhiyuan Liu +2 more
TL;DR: This study proposes an interesting electric vehicle fleet size and trip pricing (EVFS&TP) problem for one-way carsharing services by taking into account the necessary practical requirements of vehicle relocation and personnel assignment by developing a mixed-integer nonlinear and nonconvex programming model.