Optimal Stacked Sparse Autoencoder Based Traffic Flow Prediction in Intelligent Transportation Systems-Reference-Cited by-同舟云学术

Optimal Stacked Sparse Autoencoder Based Traffic Flow Prediction in Intelligent Transportation Systems

Published:2022 Issue: Volume: Page:111-127
ISSN:2198-4182
Container-title:Virtual and Augmented Reality for Automobile Industry: Innovation Vision and Applications
language:
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Author:

Neelakandan S.,Prakash M.,Bhargava Sanjay,Mohan Kumar,Robert Nismon Rio,Upadhye Sachin

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-94102-4_6

Reference20 articles.

1. Boukerche, A., Tao, Y., Sun, P.: Artificial intelligence-based vehicular traffic flow prediction methods for supporting intelligent transportation systems. Comput. Netw. 182, 107484 (2020)

2. Sun, P., Boukerche, A.: AI-assisted data dissemination methods for supporting intelligent transportation systems. Internet Technol. Lett. e169 (2020)

3. Zhang, J., Wang, F.-Y., Wang, K., Lin, W.-H., Xu, X., Chen, C.: Parallel control and management for intelligent transportation systems: concepts, architectures, and applications. IEEE Trans. Intell. Transp. Syst. 11(3), 630–638 (2010)

4. Wang, F.-Y.: Toward a revolution in transportation operations: AI for complex systems. IEEE Intell. Syst. 23(6), 8–13 (2008)

5. Iordanidou, G., Papamichail, I., Roncoli, C., Papageorgiou, M.: Feedback-based integrated motorway traffic flow control with delay balancing. IEEE Trans. Intell. Transp. Syst. 18(9), 2319–2329 (2017)

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