论文标题
使用动态图预测花旗自行车需求的演变
Predicting Citi Bike Demand Evolution Using Dynamic Graphs
论文作者
论文摘要
自行车共享系统通常由于需求变化而遭受能力管理差。这些自行车共享系统将受益于预测需求的模型，以减少每个站点存储的自行车数量。在本文中，我们尝试采用图形神经网络模型来预测纽约市花旗自行车数据集的自行车需求。
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.
