… Spatio-Temporal Urban Travel Demand Forecasting Model (STUTDFM). The architecture of
the model consists of an external factor influence component, a spatio-temporal … urban travel …

… learning and meta⁃learning to predict travel time. The method is composed of a spatio ⁃
temporal network model and a meta ⁃ learning … ,deep learning,meta learning,spatio⁃temporal …

… transportation. In order to fully exploit the spatial correlation between nodes in a traffic network,
this paper proposes a deep spatio-temporal … proposes to abstract the traffic network as a …

… was utilized to predict traffic flow and obtain the final prediction values. The validity of the
model was verified on the New York City Taxi dataset and the New York City Bike dataset. …

… Urban traffic prediction from spatio-temporal data using deep meta learning[C]//ACM.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and …

… Linear mixed effects models Higher traffic-related air pollution made children a smaller
improvement in cognitive development Sunyer … Urban traffic ultrafine particulate matter …

… Urban traffic prediction from spatio-temporal data using deep meta learning[C]//Proceedings
of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, …

… interpolation and short-term traffic forecasting. Previous studies model the traffic correlations
… However, the distance-based methods neglect the spatio-temporal heterogeneity of traffic …

… Fu 等[25] 提出的DeepIST (deep image-based spatiotemporal) 模型, 使用图像处理领域的方法
来进行时间预测: 先将车辆轨迹分段, 每一段轨迹构造出多 张图像, 分别包含交通状态,交通信号…

… of traffic congestion problems and accidents in cities. Therefore, it is essential for urban traffic
… to perceive the travel time of a given urban path. Previous methods always perceived the …