A novel hybrid method for achieving accurate and timeliness vehicular traffic flow prediction in road networks
The efficient and smooth operation of the transportation system is crucial for ensuring the
normal functioning of modern society and people's daily lives. However, the increase in …
normal functioning of modern society and people's daily lives. However, the increase in …
St-mlp: A cascaded spatio-temporal linear framework with channel-independence strategy for traffic forecasting
The criticality of prompt and precise traffic forecasting in optimizing traffic flow management
in Intelligent Transportation Systems (ITS) has drawn substantial scholarly focus. Spatio …
in Intelligent Transportation Systems (ITS) has drawn substantial scholarly focus. Spatio …
Large Language Models for Mobility in Transportation Systems: A Survey on Forecasting Tasks
Mobility analysis is a crucial element in the research area of transportation systems.
Forecasting traffic information offers a viable solution to address the conflict between …
Forecasting traffic information offers a viable solution to address the conflict between …
Sfl: A high-precision traffic flow predictor for supporting intelligent transportation systems
As a potential solution to the growing conflict between the increasing demand for
transportation and the limited capacity of transportation infrastructure, Intelligent …
transportation and the limited capacity of transportation infrastructure, Intelligent …
Daily Physical Activity Monitoring--Adaptive Learning from Multi-source Motion Sensor Data
In healthcare applications, there is a growing need to develop machine learning models that
use data from a single source, such as that from a wrist wearable device, to monitor physical …
use data from a single source, such as that from a wrist wearable device, to monitor physical …
SST: A Simplified Swin Transformer-based Model for Taxi Destination Prediction based on Existing Trajectory
Accurately predicting the destination of taxi trajectories can have various benefits for
intelligent location-based services. One potential method to accomplish this prediction is by …
intelligent location-based services. One potential method to accomplish this prediction is by …
ST-GIN: An uncertainty quantification approach in traffic data imputation with spatio-temporal graph attention and bidirectional recurrent united neural networks
Traffic data serves as a fundamental component in both research and applications within
intelligent transportation systems. However, real-world transportation data, collected from …
intelligent transportation systems. However, real-world transportation data, collected from …
RW-STT: random walk embedded spatial-temporal transformer networks for traffic flow forecasting
W Kong, Y Ju, J Luo, J Wang… - … Conference on Control …, 2023 - ieeexplore.ieee.org
Predicting traffic patterns is crucial for urban traffic management and planning, which
predicts future traffic data based on current traffic conditions. To acquire better prediction …
predicts future traffic data based on current traffic conditions. To acquire better prediction …