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Modelling of ambient noise levels in urban environment

EasyChair Preprint no. 2096

5 pagesDate: December 5, 2019

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, noise monitoring, Support Vector Machine

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@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 no. 2096},

  year = {EasyChair, 2019}}
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