Modelling of ambient noise levels in urban environment

EasyChair Preprint 2096

Abstract

The study conducts time-series approach for analysing one year noise monitoring data. Support Vector Machine (SVM) technique is used as a modelling technique for time-series approach. The noise data is trained using 10-fold cross validation to get optimum hyper-parameters (γ, ε, C). The performance and accuracy of model is determined by statistical parameters like MSE, RMSE, MAPE in %, R². The paper predicts an error of ± 2dB(A) with the implementation of Support Vector Machine (SVM). 

Keyphrases: Ambient Noise Level, Support Vector Machine, noise monitoring

@booklet{EasyChair:2096,
  author    = {Shashi Kant Tiwari and L.A Kumaraswamidhas and Naveen Garg},
  title     = {Modelling of ambient noise levels in urban environment},
  howpublished = {EasyChair Preprint 2096},
  year      = {EasyChair, 2019}}