LGDec 18, 2022
Predicting Citi Bike Demand Evolution Using Dynamic Graphs
arXiv:2212.09175v1h-index: 30
Originality Synthesis-oriented
AI Analysis
This work addresses capacity management for bike sharing systems, but appears incremental as it applies an existing method to a specific dataset.
The paper tackled the problem of variable demand in bike sharing systems by applying a graph neural network model to predict bike demand in the NYC Citi Bike dataset, but no concrete results or numbers were provided.
Bike sharing systems often suffer from poor capacity management as a result of variable demand. These bike sharing systems would benefit from models to predict demand in order to moderate the number of bikes stored at each station. In this paper, we attempt to apply a graph neural network model to predict bike demand in the New York City, Citi Bike dataset.