A Hybrid Deep Learning Approach for Traffic Flow Prediction in Highway Domain-Reference-Cited by-同舟云学术

A Hybrid Deep Learning Approach for Traffic Flow Prediction in Highway Domain

Published:2021 Issue: Volume: Page:253-267
ISSN:1867-8211
Container-title:Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
language:
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Author:

Wang Zhe,Ding Weilong^ORCID,Wang Hui

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-67540-0_15

Reference30 articles.

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2. Ding, W., Zhang, S., Zhao, Z.: A collaborative calculation on real-time stream in smart cities. Simul. Model. Pract. Theory 73(4), 72–82 (2017)

3. Wang, X., Ding, W.: A short-term traffic prediction method on big data in highway domain. J. Comput. Appl. 39(01), 93–98 (2019)

4. Zheng, Y., Capra, L., Wolfson, O., et al.: Urban computing: concepts, methodologies, and applications. ACM Trans. Intell. Syst. Technol. (TIST) 5(3), 1–55 (2014)

5. Smith, B.L., Demetsky, M.J.: Traffic flow forecasting: comparison of modeling approaches. J. Transp. Eng. 123(4), 261–266 (1997)

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1. Geographic and Temporal Deep Learning Method for Traffic Flow Prediction in Highway Network;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2021