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Urban Origin–Destination Travel Time Estimation Using K-Nearest-Neighbor-Based Methods

Improving the estimation of origin–destination (O-D) travel times poses a formidable challenge due to the intricate nature of transportation dynamics. Current deep learning models often require an overwhelming amount of data, both in terms of data points and variables, thereby limiting their applica...

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Principais autores: Felipe Lagos, Sebastián Moreno, Wilfredo F. Yushimito, Tomás Brstilo
Format: Artigo
Sprog:Inglês
Udgivet: MDPI AG 2024-04-01
Serier:Mathematics
Fag:
origin–destination travel time
machine learning
k-nearest neighbor
adaptive algorithm
haversine distance
Online adgang:https://www.mdpi.com/2227-7390/12/8/1255
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