odinhg/Graph-Neural-Networks-INF367A
Traffic prediction with graph neural network using PyTorch Geometric. The implementation uses the MetaLayer class to build the GNN which allows for separate edge, node and global models.
This project helps traffic engineers and urban planners predict future traffic volumes on specific road segments. By taking current traffic data, alongside month, weekday, and hour, it forecasts traffic for the next hour for each station. It's designed for professionals who need accurate short-term traffic flow predictions for operational planning.
No commits in the last 6 months.
Use this if you need to predict hourly traffic volumes across a network of interconnected traffic stations.
Not ideal if you need long-range traffic forecasts or predictions for individual, isolated road segments without network dependencies.
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Language
Python
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Last pushed
Feb 02, 2024
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