Proceedings of the 7th International Conference on Civil Engineering for Sustainable Development (ICCESD 2024)

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Assessment of Traffic Induced Noise in Dhaka Using an Artificial Neural Network Approach

Authors
Syeda Aniqa Anjum1, *, Musbiha Rahman Meehan1, A. B. M. Badruzzaman2
1Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
2Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
*Corresponding author. Email: aniqarafa@gmail.com
Corresponding Author
Syeda Aniqa Anjum
Available Online 23 July 2024.
DOI
10.2991/978-94-6463-478-5_7How to use a DOI?
Keywords
artificial neural network; noise pollution; vehicle-noise correlation
Abstract

In Dhaka, urbanization is growing at a rapid rate which has brought about an increase in road traffic, resulting in a significant rise in noise pollution levels. This study aims to assess the relationship among various vehicle types and the noise generated by these vehicles. Study locations were set near educational institutions and hospitals as these are noise sensitive areas. To assess the noise pollution levels, data were collected at several locations throughout the week. The average Leq in the morning and afternoon hours were found to be higher than the standard level of 60dB set by the Department of Environment in Bangladesh, indicating the severity of the noise pollution problem. For further analysis, a multilayer feed forward artificial neural network model was developed which was trained using Bayesian Regularization (BR) algorithm. The model was used to predict Leq and L10 in dB and used hourly volume data of different vehicle types, including heavy, medium, light, and non-motorized vehicles as well as road width as input variables. The regression value obtained from the model indicated a moderate correlation (R=0.75) between the inputs and outputs. From further analysis light vehicles were found to be the biggest contributor of noise pollution in these areas.

Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 7th International Conference on Civil Engineering for Sustainable Development (ICCESD 2024)
Series
Atlantis Highlights in Engineering
Publication Date
23 July 2024
ISBN
10.2991/978-94-6463-478-5_7
ISSN
2589-4943
DOI
10.2991/978-94-6463-478-5_7How to use a DOI?
Copyright
© 2024 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Syeda Aniqa Anjum
AU  - Musbiha Rahman Meehan
AU  - A. B. M. Badruzzaman
PY  - 2024
DA  - 2024/07/23
TI  - Assessment of Traffic Induced Noise in Dhaka Using an Artificial Neural Network Approach
BT  - Proceedings of the 7th International Conference on Civil Engineering for Sustainable Development (ICCESD 2024)
PB  - Atlantis Press
SP  - 78
EP  - 92
SN  - 2589-4943
UR  - https://doi.org/10.2991/978-94-6463-478-5_7
DO  - 10.2991/978-94-6463-478-5_7
ID  - Anjum2024
ER  -