Research for Predicting the Underwater Acoustic Performance of Sandwich Structural Composite Based on Support Vector Machine

Yong Qing Li; Xi Zhu; Fang Xu

doi:10.4028/www.scientific.net/AMR.308-310.678

Paper Titles

Self-Assembly of Flower-Like CeO₂ Microspheres via a Template-Free Synthetic Approach and its Use as Support in Enhanced CO and Benzene Oxidation Activity
p.656

Attitude Resolution Algorithm of Gyro-Free Inertial Navigation System
p.662

Magic Cube Approach Application on Crashworthiness Design of Front Rail for Weight Reduction
p.668

Study on the Mechanical Characteristics of Multilayer Piezoelectric Stack Actuator
p.674

Research for Predicting the Underwater Acoustic Performance of Sandwich Structural Composite Based on Support Vector Machine
p.678

Effect of the Grain Size on Magnetic Properties of Nanocrystalline CoFe₂O₄ Ferrite
p.685

Synthesis of Chiral Amphiphilic Graft Copolymer PBTQMO-g-MPEO
p.689

Study on Transverse Cooling Uniformity in Controlled Cooling Process of Copper Plate
p.692

Effect of Dipolar Side Groups on Conformational Properties of Heteroatom Polymers
p.696

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 308-310Research for Predicting the Underwater Acoustic...

Research for Predicting the Underwater Acoustic Performance of Sandwich Structural Composite Based on Support Vector Machine

Abstract:

Support vector machine(SVM) is a new learning machine based on the statistical learning theory. For it not only has solid theory, but also can solve many practical problems in optimizing area, such as small samples, over learning, high dimension and local minima. And has shown attractive potential and promising performance in a wide range of fields and applications. In this paper, the least square support vector machine(LS-SVM), which developed from normal SVM, has been used for predicting and modeling the underwater acoustic performance of sandwich composite plates, which were composed of fiber-reinforced plastics/acoustic rubber/fiber-reinforced plastics. Effective result indicate that LS-SVM is of potential application in sandwich structural composite design and acoustic material research.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 308-310)

Pages:

678-684

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.308-310.678

Citation:

Cite this paper

Online since:

August 2011

Authors:

Yong Qing Li, Xi Zhu, Fang Xu

Keywords:

Composite Plates, Modeling, Support Vector Machine (SVM), Underwater Acoustic Performance

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Bai Guofeng. The sound absorption mechanism research of underwater anechoic tile[D]. The master degree paper of Harbin University of Engineering, 2002.( in Chinese)

Google Scholar

[2] V. N. Vapnik. An overview of statistical learning theory. IEEE Trans. Neural Networks, Vol. 10, pp.988-999，1999.

Google Scholar

[3] R. Kumar, A. Kulkarni, V. K. Jayaraman and B. D. Kulkarni. Symbolization assisted SVM classifier for noisy data. Pattern Recognition Letters, Vol. 25, Issue 4, pp.495-504, March 2004.

DOI: 10.1016/j.patrec.2003.12.012

Google Scholar

[4] Suykens J A K, Vandewalle J. Least squares support vector machines classifiers [J]. Neural Network Letters, 1999, l9(3): 293-300.

Google Scholar

[5] Vapnik V N. The Nature of statistical Learning Theory [M]. New York: Springer-Verlag,1999. Second Edition.

Google Scholar

[6] Bishop C M. Neural Networks for Pattern Reorganization [M]. Oxford University Press, 1995.

Google Scholar