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Spatiotemporal expert GPT network for traffic flow prediction

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Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering

Published online on

Abstract

Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, Ahead of Print.
Urban traffic displays pronounced temporal periodicity, spatial dependencies, and heterogeneous behavioral patterns. These characteristics hinder traditional approaches from capturing multi-scale dynamics and complex topologies within a unified prediction ...