Scientific paper ID 1477 : 2017/3

Jelena Tomić, Nebojša Bogojević, Zlatan Šoškić

Road traffic represents one of the main sources of noise pollution in urban areas. In order to control noise levels it is necessary to have a suitable calculation method for traffic noise prediction. Since 1950s many mathematical models for estimation of traffic noise pollution have been developed, and most of available models found in literature are based on regression analysis. This paper presents the application of particle swarm optimization in developing of simple mathematical model for prediction of equivalent A-weighted level of road traffic noise in urban areas of the city of Niš, Serbia. Predictions of the developed mathematical model are compared to experimental data collected by traffic noise measurements, as well as to predictions of commonly used traffic noise models, and the obtained results of statistical analysis of differences between measured and calculated noise levels are presented in this paper.

шумозамърсяване прогнозиране на шума оптимизация на роговите частици.Traffic noise Noise prediction Particle swarm optimizationJelena Tomić Nebojša Bogojević Zlatan Šoškić


[1] De Vos, P., Licitra, G. “Noise maps in the European Union: An overview”. In Licitra, G. (Ed.), Noise mapping in EU: Models and Procedures, pp. 285–310, USA: CRC Press, 2013.

[2] Ohrstrom, E., Rylander, R. “Sleep disturbance by road traffic noise - A laboratory study on number of noise events”. Journal of Sound and Vibration, vol. 143, no. 1, pp. 93–101, 1990.

[3] Fyhri, A., Klboe, R. “Road traffic noise, sensitivity, annoyance and self-reported health - A structural equation model exercise”. Environment International, vol. 35, no. 1, pp. 91-97, 2009.

[4] Pirreera, S., Valck, E. D., Cluydts, R. “Nocturnal road traffic noise: A review on its assessment and consequences on sleep and health”. Environment International, vol. 36, no. 5, pp. 492–498, 2010.

[5] Theebe, M. A. “Planes, trains, and automobiles: The impact of traffic noise on house prices”. Journal of Real Estate Finance and Economics, vol. 28, no. 2, pp. 209–234, 2004.

[6] Cammarata, G ., Cavalieri, S., Fichera, A. “A neural network architecture for noise prediction”. Neural Networks, vol. 8, no. 6, pp. 963-973, 1995.

[7] Genaro, N., Torija, A., Ramos-Ridao, A., Requena, I., Ruiz, DP., Zamorano, M. “A neural network based model for urban noise prediction”. The Journal of the Acoustical Society of America, vol. 128, pp. 1738-1746, 2010.

[8] Givargis, S., Karimi, H. “A basic neural traffic noise prediction model for Tehran’s roads”. Journal of Environmental Management, vol. 91, pp. 2529-2534, 2010.

[9] Gundogdu, O., Gokdag, M., Yuksel, F. “A traffic noise prediction method based on vehicle composition using genetic algorithms”. Applied Acoustics, vol. 66, no. 7, pp. 799-809, 2005.

[10] Rahmani, S., Mousavi, S., Kamali, M. J. “Modeling of road-traffic noise with the use of genetic algorithm”. Applied Soft Computing, vol. 11, no. 1, pp. 1008-1013, 2011.

[11] Quartieri J., Mastorakis N. E., Iannone G., Guarnaccia C., D’Ambrosio S., Troisi A., Lenza T.L.L. “A Review of Traffic Noise Predictive Models”, Proc. of the 5th WSEAS Int. Conf. on “Applied and Theoretical Mechanics” (MECHANICS”09), Puerto De La Cruz, Canary Islands, Spain, December 14-16, 2009. ISBN: 978-960-474-140-3 / ISSN: 1790-2769, pp. 72-80.

[12] C. G. Balachandran. “Urban Traffic Noise in Environmental Impact Assesssments”. In: Proceedings of 14th International Congreess on Acoustic, paper E1-4, Bejeing, China, 1992.

[13] Burgess, M. A. “Noise prediction for Urban Traffic Conditions - Related to Measurement in Sydney Metropolitan Area”. Applied Acoustics, vol. 10, pp. 1-7, 1977.

[14] Griffiths, I. D., Langdon, F. J. “Subjective Response to road traffic noise”. Journal of Sound and Vibration, vol. 8, pp. 16-32, 1968.

[15] Fagotti, C., Poggi, A. “Traffic Noise Abatement Strategies. The Analysis of Real Case not Really Effective”, in Proc. of 18th International Congress for Noise Abatement, pp. 223-233, Bologna, Italy, 1995.

[16] Kennedy, J., Eberhart, R., “Particle swarm optimization”. In Proc. of IEEE international conference on neural network, pp. 1942-1948, 1995.




This site uses cookies as they are important to its work.

Accept all cookies
Cookies Policy