C.W. Xiao
College of Automotive Engineering, Shanghai University of Engineering Science, 201620, Shanghai, People�s Republic of China
Y.S. Wang
College of Automotive Engineering, Shanghai University of Engineering Science, 201620, Shanghai, People�s Republic of China
L. Shi
College of Automotive Engineering, Shanghai University of Engineering Science, 201620, Shanghai, People�s Republic of China
H. Guo
College of Automotive Engineering, Shanghai University of Engineering Science, 201620, Shanghai, People�s Republic of China
ABSTRACT
Based on Least Square Support Vector Machine (LSSVM) algorithm, a Sound Quality Prediction (SQP) model of vehicle interior noise during acceleration is presented in this study. The objective psychoacoustic parameters and subjective annoyance results are used as the input and output of the model, respectively. With correlation analysis, some psychoacoustic parameters, such as loudness, sharpness, roughness, articulation index and tonality, are selected for the modeling. The estimated values of unknown samples with the LSSVM SQP model are highly correlated with the subjective annoyance values, which has a higher accuracy than that with Multiple Linear Regression (MLR) model. Results show that the proposed LSSVM SQP model has good generalization ability and can be applied to the sound quality prediction of vehicle interior noise during acceleration.
PDF References Citation
How to cite this article
C.W. Xiao, Y.S. Wang, L. Shi and H. Guo, 2013. Sound Quality Prediction of Vehicle Interior Noise During Acceleration Using Least Square Support Vector Machine. Journal of Applied Sciences, 13: 2288-2293.
DOI: 10.3923/jas.2013.2288.2293
URL: https://scialert.net/abstract/?doi=jas.2013.2288.2293
DOI: 10.3923/jas.2013.2288.2293
URL: https://scialert.net/abstract/?doi=jas.2013.2288.2293
REFERENCES
- Gao, Y.H., Q. Sun, J. Liang and R.J. Tang, 2010. Evaluation method and mathematical model of vehicle interior sound quality during acceleration. J. Jilin Univ.: Eng. Sci., 40: 1502-1506.
Direct Link - Gonzalez, A., M. Ferrer, M. Diego, G. Pinero and J.J. Garcia-Bonito, 2003. Sound quality of low-frequency and car engine noises after active noise control. J. Sound Vib., 265: 663-679.
CrossRefDirect Link - Lee, S.K., 2008. Objective evaluation of interior sound quality in passenger cars during acceleration. J. Sound Vib., 310: 149-168.
CrossRefDirect Link - Nor, M.J.M., M.H. Fouladi, H. Nahvi and A.K. Ariffin, 2008. Index for vehicle acoustical comfort inside a passenger car. Applied Acoust, 69: 343-353.
CrossRefDirect Link - Yıldırım, S. and I. Eski, 2008. Sound quality analysis of cars using hybrid neural networks. Simulation Modell. Practice Theory, 16: 410-418.
CrossRefDirect Link - Suykens, J.A.K. and J. Vandewalle, 1999. Least squares support vector machine classifiers. Neural Process. Lett., 9: 293-300.
CrossRefDirect Link - Wang, Y.S., C.M. Lee, D.G. Kim and Y. Xu, 2007. Sound-quality prediction for nonstationary vehicle interior noise based on wavelet pre-processing neural network model. J. Sound Vib., 299: 933-947.
CrossRefDirect Link