COMPARISON OF ANN AND ANALYTICAL MODELS IN TRAFFIC NOISE MODELING AND PREDICTIONS
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN ENGINEERING AND TECHNOLOGY
Author(s): P. DHIMAN , S.K.MANGAL
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.
- Publication Date: 25-May-2014
- DOI: 10.15224/978-1-63248-028-6-03-67
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A MULTIPLE REGRESSION MODEL FOR URBAN TRAFFIC NOISE IN DELHI
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN ENGINEERING AND TECHNOLOGY
Author(s): P. DHIMAN , S.K.MANGAL
Abstract: This paper reviews the strategies so far recommended for modeling road traffic noise in India. An analytical model is developed to predict road traffic noise for busy roads of Delhi, India. Equivalent continuous sound pressure level, LAeqT is analyzed at different busy road locations of Delhi. A multiple linear regression analysis is conducted to predict the noise metrics LAeq, TNI and NPL in terms of traffic flow rate, percentage of heavy vehicles, and average traffic speeds. The model so developed is validated with actual experimental data.
- Publication Date: 25-May-2014
- DOI: 10.15224/978-1-63248-028-6-03-68
- Views: 0
- Downloads: 0