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Comparison of ANN and Analytical Models in Traffic Noise Modeling and Predictions

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Abstract

This paper demonstrates the applications of artificial neural networks to predict the equivalent continuous sound level \((L_\mathrm{Aeq})\) and 10 Percentile exceeded sound level \((L_\mathrm{10})\) generated due to traffic noise for various locations in Delhi. A Model based on back-propagation neural network was trained, validated, and tested using the measured data. The work shows that the model is able to produce accurate predictions of hourly traffic noise levels. A comparative study shows that neural networks out-perform the multiple linear regression models developed in terms of total traffic flow and equivalent traffic flow. The prediction model proposed in the study may serve as a vital tool for traffic noise forecasting and noise abatement measures to be undertaken for Delhi city.

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Acknowledgments

Authors are extremely thankful to the anonymous reviewers for their helpful comments and suggestions especially pertaining to ANN modeling. Authors thank M.Tech scholars-Manoj and Rahul; B.Tech students: Mr. Fahed, Mr. Zaimul and Mr. Ateeq; M. Tech student-Mr. Sumit for helping in traffic noise monitoring from May, 2014 to June, 2015. Authors also thank Late Dr. T. K. Saxena for his support in this study. Author thanks Mrs. Vishesh, Amity Engg. College, New Delhi for her help in Matlab use & analysis. Financial allocation by CSIR under project OLP 071132 for procurement of a Noise Monitoring System is greatly acknowledged.

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Authors and Affiliations

  1. CSIR-National Physical Laboratory, New Delhi, 110012, India

    N. Garg

  2. PEC University of Technology, Sector-12, Chandigarh, 160 012, India

    S. K. Mangal & P. Dhiman

  3. National Institute of Technology, Kurukshetra, 136 119, India

    P. K. Saini

  4. Department of Mechanical & Production Engineering, Delhi Technological University, New Delhi, 110 042, India

    N. Garg & S. Maji

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  1. N. Garg
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Correspondence to N. Garg.

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Garg, N., Mangal, S.K., Saini, P.K. et al. Comparison of ANN and Analytical Models in Traffic Noise Modeling and Predictions. Acoust Aust 43, 179–189 (2015). https://doi.org/10.1007/s40857-015-0018-3

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