13 citations · 14 across the 5 of their papers we have counts for
5 papers
Effective Online 3D Bin Packing with Lookahead Parcels Using Monte Carlo Tree Search
Jiangyi Fang, Bowen Zhou, Haotian Wang +2
Online 3D Bin Packing (3D-BP) with robotic arms is crucial for reducing transportation and labor costs in modern logistics. While Deep Reinforcement Learning (DRL) has shown strong…
STContext: A Multifaceted Dataset for Developing Context-aware Spatio-temporal Crowd Mobility Prediction Models
Liyue Chen, Jiangyi Fang, Tengfei Liu +2
In smart cities, context-aware spatio-temporal crowd flow prediction (STCFP) models leverage contextual features (e.g., weather) to identify unusual crowd mobility patterns and enh…
A Unified Model for Spatio-Temporal Prediction Queries with Arbitrary Modifiable Areal Units
Liyue Chen, Jiangyi Fang, Tengfei Liu +2
Spatio-Temporal (ST) prediction is crucial for making informed decisions in urban location-based applications like ride-sharing. However, existing ST models often require region pa…
A Data-driven Region Generation Framework for Spatiotemporal Transportation Service Management
Liyue Chen, Jiangyi Fang, Zhe Yu +3
MAUP (modifiable areal unit problem) is a fundamental problem for spatial data management and analysis. As an instantiation of MAUP in online transportation platforms, region gener…
UCTB: An Urban Computing Tool Box for Building Spatiotemporal Prediction Services
Jiangyi Fang, Liyue Chen, Di Chai +4
Spatiotemporal crowd flow prediction is one of the key technologies in smart cities. Currently, there are two major pain points that plague related research and practitioners. Firs…