Modelling and evaluation of light railway system’s noise using neural predictors

Journal of Environmental Health Science Engineering

Bülent Bostancı²  Abdurrahman Geymen²  Selçuk Erkaya¹ 

[1] Engineering Faculty, Mechatronics Engineering Department, Erciyes University, Kayseri 38039, Turkey;Engineering Faculty, Geomatics Engineering Department, Erciyes University, Kayseri 38039, Turkey

关键词: Radial basis function;    Neural networks;    Noise mapping;   

Others  :  1161193
DOI  :  10.1186/s40201-015-0173-3

 received in 2014-09-26, accepted in 2015-03-03,  发布年份 2015

【 摘 要 】

Background

Noise is defined as a sound or series of sounds that are considered to be invasive, irritating, objectionable and disruptive to the quality of daily life. Noise is one of the environmental pollutants, and in cities it is usually originated from road traffic, railway traffic, airports, industry etc. The tram is generally considered as environmentally friendly, namely non-polluting and silent. However complaints from residents living along the tramway lines prove that it may sometimes cause annoyance. In this study, a Global Pointing System (GPS) receiver for determining the sampling locations and a frequency based noise measurement system for collecting the noise data are used to analyse the noise level in the city centre. Both environmental (background) and tram noises are measured.

Results

Three types of neural networks are used to predict the noises of the tram and environment. The results of three approaches indicate that the proposed neural network with Radial Basis Function (RBF) has superior performance to predict the noises of the tram and environment.

Conclusions

For making a decision about transportation planning, this network model can help urban planners for evaluating and/or isolating the tram noise in terms of human health.

【 授权许可】

   
2015 Erkaya et al.; licensee BioMed Central.

【 图 表 】

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