The application of Principal Component Analysis to materials science data
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概要
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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.
- CODATAの論文
著者
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Li Xiang
Department Of Animal Science Yanbian University
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Li Xiang
Department of Materials Science and Engineering and Faculty of Information Technology Rensselaer Polytechnic Institute
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Suh Changwon
Department of Materials Science and Engineering and Faculty of Information Technology Rensselaer Polytechnic Institute
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Rajagopalan Arun
Department of Materials Science and Engineering and Faculty of Information Technology Rensselaer Polytechnic Institute
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Rajan Krishna
Department of Materials Science and Engineering and Faculty of Information Technology Rensselaer Polytechnic Institute
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