🌎 🚙📚 Predicting travel times and traffic density on a highway in Slovenia
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Updated
Jun 7, 2024 - CSS
🌎 🚙📚 Predicting travel times and traffic density on a highway in Slovenia
[ICML'2024] "FlashST: A Simple and Universal Prompt-Tuning Framework for Traffic Prediction"
LibCity: An Open Library for Urban Spatial-temporal Data Mining
[Pattern Recognition] Decomposition Dynamic Graph Conolutional Recurrent Network for Traffic Forecasting
This work considers combine multi-tricks with highway network to achieve traffic flow prediction accurately.
M-LibCity: An Open Source Library for Urban Spatio-temporal Prediction Models Based on MindSpore
ST-SSL (STSSL): Spatio-Temporal Self-Supervised Learning for Traffic Flow Forecasting/Prediction
Attention Feature Fusion base on spatial-temporal Graph Convolutional Network(AFFGCN)
A project leverages external data (traffic incidents, weather) to predict traffic flow. Graph is used to model the complex relationship of data.
Traffic prediction is the task of predicting future traffic measurements (e.g. volume, speed, etc.) in a road network (graph), using historical data (timeseries).
[AAAI2023] A PyTorch implementation of PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction.
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)
ST-MAN: Spatio-Temporal Multimodal Attention Network for Traffic Prediction (KSEM 2023)
Traffic Flow Prediction with Neural Networks(SAEs、LSTM、GRU).
A PyTorch implementation of T-GCN
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.
Summary of open source code for deep learning models in the field of traffic prediction
2022年讯飞开发者大赛-考虑时空依赖及全局要素的城市道路交通流量预测挑战赛-Top3解决方案
Predict traffic flow by affinity propagation clustering and LSTM
Pytorch implementation of Spatio-temporal Differential Equation Network (STDEN).
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