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...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2005
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| Online Access: | http://psasir.upm.edu.my/id/eprint/39007/ http://psasir.upm.edu.my/id/eprint/39007/1/39007.pdf |
| _version_ | 1848849028760993792 |
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| author | Zamani, Seyed Ali Mahmud, Ahmad Rodzi Jahanshiri, Ebrahim Hussien, Rabie Ali Karimadini, Mohammad |
| author_facet | Zamani, Seyed Ali Mahmud, Ahmad Rodzi Jahanshiri, Ebrahim Hussien, Rabie Ali Karimadini, Mohammad |
| author_sort | Zamani, Seyed Ali |
| building | UPM Institutional Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-15T09:43:53Z |
| format | Conference or Workshop Item |
| id | upm-39007 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T09:43:53Z |
| publishDate | 2005 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-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. . |
| spellingShingle | Zamani, Seyed Ali Mahmud, Ahmad Rodzi Jahanshiri, Ebrahim Hussien, Rabie Ali Karimadini, Mohammad Intelligent prediction of traffic volume distribution |
| title | 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_short | Intelligent prediction of traffic volume distribution |
| title_sort | intelligent prediction of traffic volume distribution |
| url | http://psasir.upm.edu.my/id/eprint/39007/ http://psasir.upm.edu.my/id/eprint/39007/1/39007.pdf |