⚠️[Deprecated] no longer maintained, please use the code inhttps://github.com/guoshnBJTU/ASTGCN-r-pytorch

Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).

A PyTorch implementation of T-GCN

[CIKM 2022] Source codes of CIKM2022 Full Paper "Domain Adversarial Spatial-Temporal Network: A Transferable Framework for Short-term Traffic Forecasting across Cities"

Long Short-Term Memory(LSTM) is a particular type of Recurrent Neural Network(RNN) that can retain important information over time using memory cells. This project includes understanding and implementing LSTM for traffic flow prediction along with the introduction of traffic flow prediction, Literature review, methodology, etc.

A time series task- predicting traffic flow using LSTM model

Multi-Attention Temporal Graph Convolution Network for Traffic Flow Forecasting

ASTGCN, LSTM, GCN LSTM with fused result from previous week, day, hour

traffic flow prediction

The repository gives case studies on short-term traffic flow forecasting strategies within the scope of my master thesis.

Cơ vu kế toán cơ thị giác đích giao thông tràng cảnh trí năng ứng dụng ( lưu lượng dự trắc bộ phân )

ML/DL-based small DIY projects.

Official repo for the following paper: Traffic Forecasting on New Roads Unseen in the Training Data Using Spatial Contrastive Pre-Training (SCPT) (ECML PKDD DAMI '23)

traffic flow prediction

Deep neural networks for daily long-term traffic flow forecasting

Pytorch implementation of Spatio-temporal Differential Equation Network (STDEN).

traffic flow prediction

traffic flow prediction

traffic flow prediction

2022 niên tấn phi khai phát giả đại tái - khảo lự thời không y lại cập toàn cục yếu tố đích thành thị đạo lộ giao thông lưu lượng dự trắc thiêu chiến tái -Top3 giải quyết phương án