Publications (29)
Minkowski-MambaNet: A Point Cloud Framework with Selective State Space Models for Forest Biomass Quantification
Jinxiang Tu, Dayong Ren, Fei Shi +4
Accurate forest biomass quantification is vital for carbon cycle monitoring. While airborne LiDAR excels at capturing 3D forest structure, directly estimating woody volume and Abov…
Multistep Speed Prediction on Traffic Networks: A Graph Convolutional Sequence-to-Sequence Learning Approach with Attention Mechanism
Zhengchao Zhang, Meng Li, Xi Lin +2
Multistep traffic forecasting on road networks is a crucial task in successful intelligent transportation system applications. To capture the complex non-stationary temporal dynami…
Enabling Time-series Foundation Model for Building Energy Forecasting via Contrastive Curriculum Learning
Rui Liang, Yang Deng, Donghua Xie +2
Advances in time-series forecasting are driving a shift from conventional machine learning models to foundation models (FMs) that are trained with generalized knowledge. However, e…
A Retrieval-Enhanced Transformer for Multi-Step Port-of-Call Sequence Prediction in Global Liner Shipping
Yanzhao Su, Fang He, Yineng Wang
Accurate multi-step port-of-call sequence prediction is vital for tactical resource orchestration and logistical efficiency. However, existing methods struggle with unreliable voya…
Simulation Comparisons of Vehicle-based and Phase-based Traffic Control for Autonomous Vehicles at Isolated Intersections
Chen Yang, Xi Lin, Meng Li +1
With the advent of autonomous driving technologies, traffic control at intersections is expected to experience revolutionary changes. Various novel intersection control methods hav…
Optimizing Drivers' Discount Order Acceptance Strategies: A Policy-Improved Deep Deterministic Policy Gradient Framework
Hanwen Dai, Chang Gao, Fang He +2
The rapid expansion of platform integration has emerged as an effective solution to mitigate market fragmentation by consolidating multiple ride-hailing platforms into a single app…
Beyond the Next Port: A Multi-Task Transformer for Forecasting Future Voyage Segment Durations
Nairui Liu, Fang He, Xindi Tang +1
Accurate forecasts of segment-level sailing durations are fundamental to enhancing maritime schedule reliability and optimizing long-term port operations. However, conventional est…
Few-Shot Learning for Dynamic Operations of Automated Electric Taxi Fleets under Evolving Charging Infrastructure: A Meta-Deep Reinforcement Learning Approach
Xiaozhuang Li, Xindi Tang, Fang He
With the rapid expansion of electric vehicles (EVs) and charging infrastructure, the effective management of Autonomous Electric Taxi (AET) fleets faces a critical challenge in env…
Metadata-Guided Adaptable Frequency Scaling across Heterogeneous Applications and Devices
Jinqi Yan, Fang He, Qianlong Sang +5
Dynamic Voltage and Frequency Scaling is essential for enhancing energy efficiency in mobile platforms. However, traditional heuristic-based governors are increasingly inadequate f…
Electrifying the Urban Taxi Fleet: A Data-driven Approach
Yikang Li, Huimiao Chen, Yanni Yang +2
This paper is devoted to proposing a data-driven approach for electrifying the urban taxi fleet. Specifically, based on the gathered real-time vehicle trajectory data of 39053 taxi…
Communication-Efficient Federated Learning for Heterogeneous Edge Devices Based on Adaptive Gradient Quantization
Heting Liu, Fang He, Guohong Cao
Federated learning (FL) enables geographically dispersed edge devices (i.e., clients) to learn a global model without sharing the local datasets, where each client performs gradien…
Network-level rhythmic control of heterogeneous automated traffic with buses
Xiangdong Chen, Xi Lin, Meng Li +1
Guaranteeing the quality of transit service is of great importance to promote the attractiveness of buses and alleviate urban traffic issues such as congestion and pollution. Emerg…
A Constraint-directed Local Search Approach to Nurse Rostering Problems
Fang He, Rong Qu
In this paper, we investigate the hybridization of constraint programming and local search techniques within a large neighbourhood search scheme for solving highly constrained nurs…
Mitigating Degree Bias in Signed Graph Neural Networks
Fang He, Jinhai Deng, Ruizhan Xue +2
Like Graph Neural Networks (GNNs), Signed Graph Neural Networks (SGNNs) are also up against fairness issues from source data and typical aggregation method. In this paper, we are p…
Dynamic Clustering for Personalized Federated Learning on Heterogeneous Edge Devices
Heting Liu, Junzhe Huang, Fang He +1
Federated Learning (FL) enables edge devices to collaboratively learn a global model, but it may not perform well when clients have high data heterogeneity. In this paper, we propo…
Online Relocating and Matching of Ride-Hailing Services: A Model-Based Modular Approach
Chang Gao, Xi Lin, Fang He +1
This study proposes an innovative model-based modular approach (MMA) to dynamically optimize order matching and vehicle relocation in a ride-hailing platform. MMA utilizes a two-la…
Data-driven Method for Estimating Aircraft Mass from Quick Access Recorder using Aircraft Dynamics and Multilayer Perceptron Neural Network
Xinyu He, Fang He, Xinting Zhu +1
Accurate aircraft-mass estimation is critical to airlines from the safety-management and performance-optimization viewpoints. Overloading an aircraft with passengers and baggage mi…
Robotic Sorting Systems: Robot Management and Layout Design Optimization
Tong Zhao, Xi Lin, Fang He +1
In the contemporary logistics industry, automation plays a pivotal role in enhancing production efficiency and expanding industrial scale. Autonomous mobile robots, in particular,…
Learning to Optimize: Joint Routing and Flow Allocation on Sparse Non-Euclidean Networks
Haomiao Sun, Fang He, Congyuan Ji +1
We study an integrated pickup-and-delivery problem on sparse, non-Euclidean networks that jointly optimizes cyclic routing, cargo flow allocation, and cross-cycle service. The tigh…
Multi-Vehicle Routing Problems with Soft Time Windows: A Multi-Agent Reinforcement Learning Approach
Ke Zhang, Meng Li, Zhengchao Zhang +2
Multi-vehicle routing problem with soft time windows (MVRPSTW) is an indispensable constituent in urban logistics distribution systems. Over the past decade, numerous methods for M…
Dynamic Pricing for Air Cargo Revenue Management
Chengyu Du, Fang He, Xi Lin
We address a dynamic pricing problem for airlines aiming to maximize expected revenue from selling cargo space on a single-leg flight. The cargo shipments' weight and volume are un…
3D Segment Anything Model with Visual Mamba for Diagnosing Placenta Accreta Spectrum
Yuliang Zhang, Fang He, Lulu Peng +5
Placenta Accreta Spectrum (PAS) is a rare but highly dangerous obstetric disease. Early and accurate PAS diagnosis is critical for maternal health. Traditional PAS diagnosis relies…
Trustworthy GNNs with LLMs: A Systematic Review and Taxonomy
Ruizhan Xue, Huimin Deng, Fang He +2
With the extensive application of Graph Neural Networks (GNNs) across various domains, their trustworthiness has emerged as a focal point of research. Some existing studies have sh…
Application of dual-sensitive decision mechanism based on queuing theory in airport taxi management
Fang He
With the rapid development of economy and global trade, flying has increasingly become the main way for people to travel, and taxi is the main transfer tool of the airport, especia…
Rhythmic Control of Automated Traffic -- Part II: Grid Network Rhythm and Online Routing
Xi Lin, Meng Li, Zuo-jun Max Shen +2
Connected and automated vehicle (CAV) technology is providing urban transportation managers tremendous opportunities for better operation of urban mobility systems. However, there…
Rhythmic Control of Automated Traffic -- Part I: Concept and Properties at Isolated Intersections
Xiangdong Chen, Meng Li, Xi Lin +2
Leveraging the accuracy and consistency of vehicle motion control enabled by the connected and automated vehicle technology, we propose the rhythmic control (RC) scheme that allows…
A Route Network Planning Method for Urban Air Delivery
Xinyu He, Fang He, Lishuai Li +2
High-tech giants and start-ups are investing in drone technologies to provide urban air delivery service, which is expected to solve the last-mile problem and mitigate road traffic…
Vehicle Dispatching and Routing of On-Demand Intercity Ride-Pooling Services: A Multi-Agent Hierarchical Reinforcement Learning Approach
Jinhua Si, Fang He, Xi Lin +1
The integrated development of city clusters has given rise to an increasing demand for intercity travel. Intercity ride-pooling service exhibits considerable potential in upgrading…
Feature Learning Viewpoint of AdaBoost and a New Algorithm
Fei Wang, Zhongheng Li, Fang He +3
The AdaBoost algorithm has the superiority of resisting overfitting. Understanding the mysteries of this phenomena is a very fascinating fundamental theoretical problem. Many studi…