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Predicting non-recurrent congestion impact: A pattern-based approach for speed drop ratio prediction using weighted K-nearest Neighbors
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DOI：10.1016/j.cie.2025.111769.png)
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Abstract
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• Pattern-based prediction of non-recurrent congestion using WK-NN and DTW. • Speed drop ratios predicted for incident and neighboring roads. • Historical pattern matching enhances interpretability for practitioners. • Real-world validation with Korean traffic and GPS data shows superiority. • Provides reliable predictions to improve traffic management and response.
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