Comparison of some methods of analyzing the three-dimensional spectral image using simulation

dc.contributor.authorSackineh Shamil Jasim
dc.date.accessioned2026-01-02T11:47:14Z
dc.date.issued2022-11-10
dc.description.abstractIn this article, a new method has been proposed in dealing with the spectral image and analyzing it under the principle components method of Three-Dimensional linearDiscriminant-Analysis (3DPCLDA) and the principle components method – QuadraticDiscriminant-Analysis (3DPCQDA) and compared it with the traditional methods, which is the principle components method - linear discriminant analysis. PCLDA) Ordinary and principal components method - Quadratic Discriminant Analysis (PCQDA), Partial Least Squares Method - PLSDA and SVM Method. Using simulation experiments, it was concluded that the three-dimensional methods are better than the traditional methods, as they have achieved the most standards of accuracy and testing
dc.formatapplication/pdf
dc.identifier.urihttps://geniusjournals.org/index.php/ejpcm/article/view/2568
dc.identifier.urihttps://asianeducationindex.com/handle/123456789/78006
dc.language.isoeng
dc.publisherGenius Journals
dc.relationhttps://geniusjournals.org/index.php/ejpcm/article/view/2568/2200
dc.sourceEurasian Journal of Physics,Chemistry and Mathematics; Vol. 12 (2022): EJPCM; 14-20
dc.source2795-7667
dc.subjectSpectral image
dc.subjectthree-dimensional analysis
dc.subjectdiscriminant analysis
dc.titleComparison of some methods of analyzing the three-dimensional spectral image using simulation
dc.typeinfo:eu-repo/semantics/article
dc.typeinfo:eu-repo/semantics/publishedVersion
dc.typePeer-reviewed Article

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