How We Can Use Multivariate Statistical Analysis to Predict Creasing of Fabrics

Katarína Zelová; Ludmila Fridrichová

doi:10.4028/www.scientific.net/AMM.543-547.1930

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 543-547How We Can Use Multivariate Statistical Analysis...

How We Can Use Multivariate Statistical Analysis to Predict Creasing of Fabrics

Abstract:

The creasing of textiles was evaluated by means of the innovative method of measuring the angle of recovery. Our aim is to find statistically significant features contributing to the determination of creasing materials. For this purpose, to identify the inner structures of data, the method of PCA analysis was used a method with latent variables. By means of PCA analysis (method of principal components) the original nine characteristics can be reduced to two latent variables, i.e. principal components. The structure and links among the examined features are characterized by methods like: Scree Plot, Score and component loading, Scatrerplot and Dendrogram.

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Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

1930-1933

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.1930

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Online since:

March 2014

Authors:

Katarína Zelová*, Ludmila Fridrichová

Keywords:

Angle of Recovery, Creasing, Linear Regression, PCA Analysis

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References

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