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Oct 2, 2023 · This technique facilitates the modeling of long-range dependencies by representing an optimal historical approximation through a high-order ...
This paper proposes a modification of traffic forecast model generated by residential and small business (SOHO, Small Office Home Office) users. The model ...
Oct 6, 2023 · ABSTRACT. Accurate traffic prediction generally depends on reliable and noise-free data, which may not reflect real-world scenarios.
Long-sequence model for traffic forecasting in suboptimal situation. M. Lablack, S. Yu, S. Xu, and Y. Shen. MobiArch, page 25-30. ACM, (2023 ).
Duration: 16:47
Posted: Sep 27, 2023
Posted: Sep 27, 2023
Missing: suboptimal | Show results with:suboptimal
5 days ago · Specifically, we propose a Heterogeneous Mixture of Experts (TITAN) model for traffic flow prediction. TITAN initially consists of three experts ...
Sequence-to-Sequence Models in Long-Term Prediction ... The design of LDEB aims to intuitively model potential influences from past traffic conditions ...
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Sep 8, 2024 · Large Language Models (LLMs) are increasingly utilized in the field of traffic management for diverse tasks such as multimodal traffic accident ...
Jul 15, 2023 · The first Transformer-like model for the Origin–Destination matrix forecasting. Crosses multiple application scenarios, covering three real-world applications.
We propose SutraNets, a novel method for neural probabilistic forecasting of long- sequence time series. SutraNets use an autoregressive generative model to ...
Missing: suboptimal | Show results with:suboptimal