摘要
在前期工作基础上,采用相关分析和主成分分析方法,对三种土的SEM照片特征块原始微结构参数进行了相关分析和主成分分析。研究表明,与域微结构参数一样,特征块微结构参数间也存在"严重"的"信息重复"现象,可以用较少主成分反映全部原始特征块微结构参数的主要信息,从而达到降维目的。
The techniques of correlation analysis and principal component analysis are utilized to study leature microstructure parameters extracted from SEM photos of the three kinds of soil. The study shows that message superposition is clear and severe among microstructure parameters for feature analysis, and that is same for field analysis. Therefore, it is reasonable to construct a lower parameter matrix to substitute the original higher parameter matrix for microstructure. The minority representative principal components can approximately synthesize the overall meaning of microstructure according to the desired value of contribution by the method of principal component analysis, and this makes extensive use of mierostructure theory in soil mechanics expediently and potentially.
出处
《岩土工程技术》
2009年第6期313-315,320,共4页
Geotechnical Engineering Technique
基金
中国博士后科学基金资助项目(20080430091)
天津市高等学校科技发展基金计划项目(20071005)
关键词
特征块微结构
SEM图像
相关分析
主成分分析
降维
feature micro-structure
SEM photo
correlation analysis
principal component analysis
dimensionality reduction
