Gct-TTE: graph convolutional transformer for travel time estimation

Gct-TTE: graph convolutional transformer for travel time estimation

Abstract This paper introduces a new transformer-based model for the problem of travel time estimation. The key feature of the proposed GCT-TTE architecture is the utilization of different data modalities capturing different properties of an input path. Along with the extensive study regarding the m...

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Bibliographic Details
Main Authors: Vladimir Mashurov, Vaagn Chopuryan, Vadim Porvatov, Arseny Ivanov, Natalia Semenova
Format: Article
Language:English
Published: SpringerOpen 2024-01-01
Series:Journal of Big Data
Subjects:
Machine learning
Graph convolutional networks
Transformers
Geospatial data
Travel time estimation
Online Access:https://doi.org/10.1186/s40537-023-00841-1

Internet

https://doi.org/10.1186/s40537-023-00841-1

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