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Neural Network (NN) Based Route Weight Computation for Bi-Directional Traffic Management System

Neural Network (NN) Based Route Weight Computation for Bi-Directional Traffic Management System
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Author(s): Shamim Akhter (East West University, Bangladesh), Rahatur Rahman (Simplexhub Ltd., Bangladesh)and Ashfaqul Islam (East West University, Bangladesh)
Copyright: 2020
Pages: 16
Source title: Deep Learning and Neural Networks: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-0414-7.ch042

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Abstract

Low-cost, flexible, easily maintainable and secure traffic management support systems are in demand. Internet-based real time bi-directional communication provides significant benefits to monitor road traffic conditions. Dynamic route computation is a vital requirement to make the traffic management system more realistic and reliable. Therefore, an integrated approach with multiple data feeds and Backpropagation (BP) Neural Network (NN) with Levenberg-Marquardt (LM) optimization is applied to predict the road weights. The results indicate that the proposed traffic system/tool with NN based dynamic weights computation is much more effective to find the optimal routes. The BP NN with LM optimization achieves 96.67% accuracy.

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