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Journal of Intelligent Transportation Systems
Technology, Planning, and Operations
Volume 21, 2017 - Issue 3
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Articles

The influence of alternative data smoothing prediction techniques on the performance of a two-stage short-term urban travel time prediction framework

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Pages 214-226 | Received 15 Jul 2015, Accepted 21 Nov 2016, Published online: 22 Feb 2017

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Lin Yu, Fangce Guo, Aruna Sivakumar & Sisi Jian. (2023) Few-Shot traffic prediction based on transferring prior knowledge from local network. Transportmetrica B: Transport Dynamics 11:1.
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Hao Wang. (2022) A Two-Stage Train Delay Prediction Method Based on Data Smoothing and Multimodel Fusion Using Asymmetry Features in Urban Rail Systems. Wireless Communications and Mobile Computing 2022, pages 1-10.
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Unsok Ryu, Jian Wang, Unjin Pak, Sonil Kwak, Kwangchol Ri, Junhyok Jang & Kyongjin Sok. (2021) A clustering based traffic flow prediction method with dynamic spatiotemporal correlation analysis. Transportation 49:3, pages 951-988.
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Wenqi Lu, Yikang Rui & Bin Ran. (2022) Lane-Level Traffic Speed Forecasting: A Novel Mixed Deep Learning Model. IEEE Transactions on Intelligent Transportation Systems 23:4, pages 3601-3612.
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Wenjun Li, Si Chen, Xiaoquan Wang, Chaoying Yin & Zhaoguo Huang. (2021) A hybrid approach for short-term traffic flow forecasting based on similarity identification. Modern Physics Letters B 35:13, pages 2150212.
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Pengshun Li, Jiarui Chang, Yi Zhang & Yi Zhang. (2021) Multi-zone prediction analysis of city-scale travel order demand. PLOS ONE 16:3, pages e0248064.
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Junyi Li, Fangce Guo, Aruna Sivakumar, Yanjie Dong & Rajesh Krishnan. (2021) Transferability improvement in short-term traffic prediction using stacked LSTM network. Transportation Research Part C: Emerging Technologies 124, pages 102977.
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Fangce Guo, John W. Polak & Rajesh Krishnan. (2018) Predictor fusion for short-term traffic forecasting. Transportation Research Part C: Emerging Technologies 92, pages 90-100.
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