How we can use multivariate statistical analysis to predict creasing of fabrics

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24410%2F14%3A%230004015" target="_blank" >RIV/46747885:24410/14:#0004015 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.4028/www.scientific.net/AMM.543-547.1930" target="_blank" >http://dx.doi.org/10.4028/www.scientific.net/AMM.543-547.1930</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.4028/www.scientific.net/AMM.543-547.1930" target="_blank" >10.4028/www.scientific.net/AMM.543-547.1930</a>

Result language
angličtina
Original language name
How we can use multivariate statistical analysis to predict creasing of fabrics
Original language description
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 theinner 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.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JJ - Other materials
OECD FORD branch
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Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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