Application of feed-forward neural networks for classifying acoustics levels in vehicle cabin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Vehicle acoustical comfort and vibration in a passenger car cabin are the main factors that attract a buyer in car purchase. Numerous studies have been carried out by automotive researchers to identify and classify the acoustics level in the vehicle cabin. The objective is to form a special benchmark for acoustics level that may be referred for any acoustics improvement purpose. This study is focused on the sound quality change over the engine speed[rpm] to recognize the noise pattern experienced in the vehicle cabin. Since it is difficult for a passenger to express, and to evaluate the noise experienced or heard in a numerical scale, a neural network optimization approach is used to classify the acoustics levels into groups of noise annoyance levels. A feed forward neural network technique is applied for classification algorithm, where it can be divided into two phases: Learning Phase and Classification Phase. The developed model is able to classify the acoustics level into numerical scales which are meaningful for evaluation purposes.

Original languageEnglish
Title of host publicationApplied Mechanics and Materials
Pages40-44
Number of pages5
Volume471
DOIs
Publication statusPublished - 2014
Event4th International Conference on Noise, Vibration and Comfort, NVC 2012 - Kuala Lumpur
Duration: 26 Nov 201228 Nov 2012

Publication series

NameApplied Mechanics and Materials
Volume471
ISSN (Print)16609336
ISSN (Electronic)16627482

Other

Other4th International Conference on Noise, Vibration and Comfort, NVC 2012
CityKuala Lumpur
Period26/11/1228/11/12

Fingerprint

Feedforward neural networks
Acoustics
Passenger cars
Acoustic noise
Vibrations (mechanical)
Railroad cars
Acoustic waves
Engines
Neural networks

Keywords

  • Acoustics level
  • Neural network optimization
  • Sound quality

ASJC Scopus subject areas

  • Engineering(all)

Cite this

Junoh, A. K., Mohd Nopiah, Z., & Mohd Ihsan, A. K. A. (2014). Application of feed-forward neural networks for classifying acoustics levels in vehicle cabin. In Applied Mechanics and Materials (Vol. 471, pp. 40-44). (Applied Mechanics and Materials; Vol. 471). https://doi.org/10.4028/www.scientific.net/AMM.471.40

Application of feed-forward neural networks for classifying acoustics levels in vehicle cabin. / Junoh, Ahmad Kadri; Mohd Nopiah, Zulkifli; Mohd Ihsan, Ahmad Kamal Ariffin.

Applied Mechanics and Materials. Vol. 471 2014. p. 40-44 (Applied Mechanics and Materials; Vol. 471).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Junoh, AK, Mohd Nopiah, Z & Mohd Ihsan, AKA 2014, Application of feed-forward neural networks for classifying acoustics levels in vehicle cabin. in Applied Mechanics and Materials. vol. 471, Applied Mechanics and Materials, vol. 471, pp. 40-44, 4th International Conference on Noise, Vibration and Comfort, NVC 2012, Kuala Lumpur, 26/11/12. https://doi.org/10.4028/www.scientific.net/AMM.471.40
Junoh, Ahmad Kadri ; Mohd Nopiah, Zulkifli ; Mohd Ihsan, Ahmad Kamal Ariffin. / Application of feed-forward neural networks for classifying acoustics levels in vehicle cabin. Applied Mechanics and Materials. Vol. 471 2014. pp. 40-44 (Applied Mechanics and Materials).
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