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pro vyhledávání: '"sparse principal component analysis (SPCA)"'
Publikováno v:
In IFAC PapersOnLine 2016 49(7):693-698
Akademický článek
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Publikováno v:
In Geochemistry March 2024
Autor:
Rahoma, Abdalhamid Ahmad
Data based methods are widely used in process industries for fault detection and diagnosis. Among the data-based methods multivariate statistical methods, for example, Principal Component Analysis (PCA), Projection to Latent Squares (PLS), and Indepe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ea095948fb4ad4c89e608f00d88e1e76
Publikováno v:
In Sustainable Energy, Grids and Networks December 2022 32
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 1419-1433 (2024)
Band selection (BS) is an effective dimensionality reduction technique for hyperspectral images. Although many relevant methods have been proposed, they often only focus on the bandwise information and the correlation between the bands, and few of th
Externí odkaz:
https://doaj.org/article/5c0b4d5553d44a2593bf2530faf65d9d
Publikováno v:
In Journal of Biomechanics 20 September 2021 126
Publikováno v:
IFAC-PapersOnLine. 49:693-698
Principal component analysis (PCA) has been widely used for data dimension reduction and process fault detection. However, interpreting the principal components and the outcomes of PCA-based monitoring techniques is a challenging task since each prin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddfcdd1434c945aa8fa846d69100f73b
https://doi.org/10.1016/j.ifacol.2016.07.259
https://doi.org/10.1016/j.ifacol.2016.07.259
Publikováno v:
In Chemometrics and Intelligent Laboratory Systems 15 March 2017 162:160-171
Publikováno v:
In Chemical Engineering Science 31 December 2021 246