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Intelligent prediction of traffic volume distribution

Traffic issues become one of the most important problems these days because of the life style of human. Therefore, paying more attention to this field seems to be essential. Distributions of traffic volume on urban roads is often described by some statistical models, which are based on probability a...

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Main Authors: Zamani, Seyed Ali, Mahmud, Ahmad Rodzi, Jahanshiri, Ebrahim, Hussien, Rabie Ali, Karimadini, Mohammad
Format: Conference or Workshop Item
Language:English
Published: 2005
Online Access:http://psasir.upm.edu.my/id/eprint/39007/1/39007.pdf
http://psasir.upm.edu.my/id/eprint/39007/
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spelling my.upm.eprints.390072016-11-08T01:52:54Z http://psasir.upm.edu.my/id/eprint/39007/ Intelligent prediction of traffic volume distribution Zamani, Seyed Ali Mahmud, Ahmad Rodzi Jahanshiri, Ebrahim Hussien, Rabie Ali Karimadini, Mohammad Traffic issues become one of the most important problems these days because of the life style of human. Therefore, paying more attention to this field seems to be essential. Distributions of traffic volume on urban roads is often described by some statistical models, which are based on probability and are suitable for ideal physical and environmental conditions. However a noticeable point is that they don't have the capability of working under complicated situations, all due to their mathematical constraints. In this paper the utilization of Neural Networks in the field of predicting traffic distribution for Petaling Jaya-an area in south west of Kuala Lumpur- is being discussed, which is applicable to a wide range of traffic situations and can play an important role in responsive urban traffic control system. A neural network-based system approach is implemented to establish an adaptive model for simulating traffic volume distribution and consequently its prediction. It has been found that Neural Networks can act strongly in the case of traffic prediction. 2005 Conference or Workshop Item NonPeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/39007/1/39007.pdf Zamani, Seyed Ali and Mahmud, Ahmad Rodzi and Jahanshiri, Ebrahim and Hussien, Rabie Ali and Karimadini, Mohammad (2005) Intelligent prediction of traffic volume distribution. In: International Advanced Technology Congress: Conference on Spatial and Computational Engineering, 6-8 Dec. 2005, Putrajaya, Malaysia. .
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Traffic issues become one of the most important problems these days because of the life style of human. Therefore, paying more attention to this field seems to be essential. Distributions of traffic volume on urban roads is often described by some statistical models, which are based on probability and are suitable for ideal physical and environmental conditions. However a noticeable point is that they don't have the capability of working under complicated situations, all due to their mathematical constraints. In this paper the utilization of Neural Networks in the field of predicting traffic distribution for Petaling Jaya-an area in south west of Kuala Lumpur- is being discussed, which is applicable to a wide range of traffic situations and can play an important role in responsive urban traffic control system. A neural network-based system approach is implemented to establish an adaptive model for simulating traffic volume distribution and consequently its prediction. It has been found that Neural Networks can act strongly in the case of traffic prediction.
format Conference or Workshop Item
author Zamani, Seyed Ali
Mahmud, Ahmad Rodzi
Jahanshiri, Ebrahim
Hussien, Rabie Ali
Karimadini, Mohammad
spellingShingle Zamani, Seyed Ali
Mahmud, Ahmad Rodzi
Jahanshiri, Ebrahim
Hussien, Rabie Ali
Karimadini, Mohammad
Intelligent prediction of traffic volume distribution
author_facet Zamani, Seyed Ali
Mahmud, Ahmad Rodzi
Jahanshiri, Ebrahim
Hussien, Rabie Ali
Karimadini, Mohammad
author_sort Zamani, Seyed Ali
title Intelligent prediction of traffic volume distribution
title_short Intelligent prediction of traffic volume distribution
title_full Intelligent prediction of traffic volume distribution
title_fullStr Intelligent prediction of traffic volume distribution
title_full_unstemmed Intelligent prediction of traffic volume distribution
title_sort intelligent prediction of traffic volume distribution
publishDate 2005
url http://psasir.upm.edu.my/id/eprint/39007/1/39007.pdf
http://psasir.upm.edu.my/id/eprint/39007/
_version_ 1643832298132471808
score 13.211869

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