The prediction of car interior steady sound quality based on dimension reduction-support vector regression

doi:10.16731/j.cnki.1671-3133.2018.11.001

Abstract

Abstract: The predictive model of Dimension Reduction-Support Vector Regression (DR-SVR) method to evaluating sound quality of car interior with small samples was proposed.The interior stable sound samples were selected as the object to analyze and its physical parameters and psychoacoustics parameters were calculated.Subjective testing was carried out via the paired comparison method,indicating that it is available to justice the merits of such samples preliminary with Psychoacoustic Annoyance (PA).Dimension reduction was achieved through factor analysis,cluster analysis and correlation analysis,then the predict model was established base on SVR method,and the correlation coefficient between predictive value and evaluated value of DR-SVR model was higher than the model without dimension reduction,verifying the method to predict subjective preferences of car interior sound with DR-SVR was effective.

Key words: support vector regression, dimension reduction, sound quality, subjective and objective evaluation, predict

CLC Number:

U461.4

Xia Xiaojun, Lai Shiyang, Xu Zhongming. The prediction of car interior steady sound quality based on dimension reduction-support vector regression[J]. Modern Manufacturing Engineering, 2018, 458(11): 1-6.

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