Paper Title:
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.

  Info
Periodical
Advanced Materials Research (Volumes 308-310)
Chapter
Product Life Cycle Design
Edited by
Jian Gao
Pages
678-684
DOI
10.4028/www.scientific.net/AMR.308-310.678
Citation
Y. Q. Li, X. Zhu, F. Xu, "Research for Predicting the Underwater Acoustic Performance of Sandwich Structural Composite Based on Support Vector Machine", Advanced Materials Research, Vols. 308-310, pp. 678-684, 2011
Online since
August 2011
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Price
$32.00
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