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Fast-TrafficNet: A hybrid model for efficient prediction of nonlinear traffic flow with sparse data

delete2025-09-17
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PRE
AI
Z
Zhihao Xu
L
Lv, Zhiqiang
李
李建波 (Jianbo Li) *
DOI：10.1016/j.chaos.2025.117230delete
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Abstract

Abstract

En 中文
• Fast-TrafficNet integrates BTD and STG-NCDE for fast nonlinear traffic prediction. • BTD reduces data dimensionality and noise via low-rank tensor decomposition. • STG-NCDE captures spatial-temporal nonlinear dynamics via continuous-time modeling.

Journal

C
Chaos Solitons and Fractals
IF:
5.6
Papers:
1.3K
Citations:
3.8W

Organization

Q
Qingdao University
Scholars:
3.1W
Papers: 2.1W
Citations: 3.7W
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