The Traffic Congestion Analysis Using Traffic Congestion Index and Artificial Neural Network in Main Streets of Electronic City (Case Study: Hamedan City)-Reference-Cited by-同舟云学术

The Traffic Congestion Analysis Using Traffic Congestion Index and Artificial Neural Network in Main Streets of Electronic City (Case Study: Hamedan City)

Published:2020-11 Issue:6 Volume:46 Page:433-442
ISSN:0361-7688
Container-title:Programming and Computer Software
language:en
Short-container-title:Program Comput Soft

Author:

ShirMohammadi Mohammad Mehdi,Esmaeilpour Mansour

Publisher

Pleiades Publishing Ltd

Subject

Software

Link

http://link.springer.com/content/pdf/10.1134/S0361768820060079.pdf

Reference46 articles.

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3. Sahoo, J., Cherkaoui, S., and Hafid, A., A novel vehicular sensing framework for smart cities, Proc. 39th IEEE Conf. on Local Computer Networks (LCN 2014), Edmonton, 2014, pp. 490–493.

4. Al-Turjman, F., Hassanein, H., and Ibnkahla, M., Efficient deployment of wireless sensor networks targeting environment monitoring applications, Comput. Commun. J., 2013, vol. 36, no. 2, pp. 135–148.

5. Al-Turjman, F., Cognitive-node architecture and a deployment strategy for the future sensor networks, Mobile Networks Appl., 2017, no. 5, pp. 1–19. https://doi.org/10.1007/s11036-017-0891-0

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