xueyan-dut/Deep-Learning-on-Traffic-Prediction
Repository for Deep Learning on Traffic Prediction: Methods, Analysis and Future Directions
This project helps urban planners, transportation engineers, and city operations managers understand and predict traffic flow patterns. It takes historical traffic data from public datasets and outputs insights into the most effective deep learning models for traffic prediction. The primary users are researchers and practitioners focused on optimizing transportation systems and mitigating congestion.
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Use this if you need to evaluate different deep learning models for forecasting traffic conditions and want to explore summarized approaches and comparative experimental results.
Not ideal if you're looking for a deployable, ready-to-use traffic prediction application without needing to delve into the underlying models and experimental setups.
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MIT
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May 31, 2021
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