학술논문
The application of Principal Component Analysis to materials science data
Document Type
article
Author
Source
Data Science Journal, Vol 1, Iss 1, Pp 19-26 (2006)
Subject
Language
English
ISSN
1683-1470
Abstract
The relationship between apparently disparate sets of data is a critical component of interpreting materials' behavior, especially in terms of assessing the impact of the microscopic characteristics of materials on their macroscopic or engineering behavior. In this paper we demonstrate the value of principal component analysis of property data associated with high temperature superconductivity to examine the statistical impact of the materials' intrinsic characteristics on high temperature superconducting behavior