Comparison of ANN and analytical models in traffic noise modeling and predictions

N., GARG and P., DHIMAN and S.K, .MANGAL (2014) Comparison of ANN and analytical models in traffic noise modeling and predictions. In: International Conference on Advances In Engineering And Technology - ICAET 2014, 24 - 25 May, 2014, RIT, Roorkee, India.

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Abstract

The major environmental challenges encountered by metropolitan cities now-a-days is the traffic noise besides air pollution. During urban planning, one thus needs methods/tools which can assist the designer in designing, planning and adoption of suitable measures for traffic noise abatement and control. The objective of the present work is to model traffic noise in terms of single-noise metrics LAeq, TNI and NPL. ANN has a capability to model complicated multi-variable functions and thus can model a system with more variables than that can be included in any other conventional models. The problem of traffic noise is non-linear in nature, so, a model based on Artificial Neural Networks (ANN) is suggested and compared with the analytical models in this work.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Traffic noise, Artificial Neural Networks, Equivalent continuous sound pressure level, L
Depositing User: Mr. John Steve
Date Deposited: 24 May 2019 12:31
Last Modified: 24 May 2019 12:31
URI: http://publications.theired.org/id/eprint/2664

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