2022
DOI: 10.1016/j.cplett.2022.139615
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The Principal Component Analysis as a tool for predicting the mechanical properties of Perovskites and Inverse Perovskites

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Cited by 8 publications
(3 citation statements)
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“…In order to differentiate between the samples of different classifications on key components with ROAV ≥ 1, PCA [ 29 ] and OPLS-DA [ 30 ] were applied, as shown in Figure 4 . According to Figure 4 A,C, pomegranate seed samples were clustered in PC1 and PC2, which correspond to 67.9% and 15.6% of the explained related variance of the data, respectively.…”
Section: Results and Analysismentioning
confidence: 99%
“…In order to differentiate between the samples of different classifications on key components with ROAV ≥ 1, PCA [ 29 ] and OPLS-DA [ 30 ] were applied, as shown in Figure 4 . According to Figure 4 A,C, pomegranate seed samples were clustered in PC1 and PC2, which correspond to 67.9% and 15.6% of the explained related variance of the data, respectively.…”
Section: Results and Analysismentioning
confidence: 99%
“…Because the principal components are orthogonal to each other, and each principal component represents different information, they can explain most of the original data information, significantly improving the efficiency of data processing. In this algorithm, the reduction of dimensions promotes the visualization of hidden attributes and the correlation of data in PC space ( Boubchir et al, 2022 ). At present, PCA is also increasingly used to explore edible crops’ different components and geographical origins.…”
Section: Machine Learningmentioning
confidence: 99%
“…Principal component analysis is one of the most widely used multivariate mathematical and statistical methods [28]. Figure 3A shows the principal component analysis (PCA) of egg yolk volatiles at different ozone treatment times, and the differences between the groups were assessed based on the contribution of the PC factors.…”
Section: Principal Component Analysis Of Egg Yolk Volatilesmentioning
confidence: 99%