Sound quality analysis of cars using hybrid neural networks


YILDIRIM Ş. , ESKİ I.

SIMULATION MODELLING PRACTICE AND THEORY, cilt.16, ss.410-418, 2008 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 16 Konu: 4
  • Basım Tarihi: 2008
  • Doi Numarası: 10.1016/j.simpat.2008.01.002
  • Dergi Adı: SIMULATION MODELLING PRACTICE AND THEORY
  • Sayfa Sayıları: ss.410-418

Özet

In this paper, a procedure of testing and evaluation on the sound quality of cars are proposed and sound quality is analysed through the cars' road running test on the providing ground, which was carried out with varying running speed. In addition to this experimental analysis, a neural network predictor is also designed to model the system for possible experimental applications. The proposed neural network is a recurrent type network, which consists of two types of neuron function in the hidden layer. As basic factors for sound quality, only objective factors are considered such as loudness, sharpness, speech intelligibility, and sound pressure level. The correlation between sound pressure level and another factor are discussed from a point of view of running speed dependency. Results of both computer simulations and experiments show that the neural predictor algorithm gives good results at accommodating different cases and provides superior prediction on two cars' sound analysis. (C) 2008 Elsevier B.V. All rights reserved.