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86 results for “Principal Component Analysis”
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Research ArticleOpen accessPhrase in the titleA Study on Factors Influencing MBA Decision After Bachelor’s Using Hybrid Model Combining ANN With Principal Component AnalysisKittipol Wisaeng, Benchalak MuangmeesriThis study comprehensively examines the complex relationship between various individual characteristics and individuals’ expectations after obtaining a bachelor’s degree, particularly in determining whether to pursue a Master of Business Administration (MBA). Utilizing a well structured, hypothesized framework, we examine several key variables directly influencing this critical decision-making process. The examined variables include, but are not limited to, demographic information, academic … …Journal of Computer Science, Vol. 21, Issue 9 · 13 Oct 2025 · 2,242 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleBotanical Composition and Yields of Forages in Natural Pastures Using Principal Component Analysis and Cluster Dendrogram in South Sulawesi, IndonesiaPurnama Isti Khaerani, Yunus Musa, Renny Fatmyah Utamy, Yasuyuki IshiiThis study aims to identify the composition and yields of forages in natural pastures using principal component analysis and cluster dendrogram in Gilireng and Majauleng subdistricts, Wajo regency, South Sulawesi, Indonesia. Pasture plants were collected using 20 randomly sampled quadrats to observe the botanical composition and yields of forages. The collected data regarding legume classification is analyzed by Multivariate Analysis … …OnLine Journal of Biological Sciences, Vol. 24, Issue 4 · 13 Jun 2024 · 5,082 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleHYPERPARAMETER SELECTION IN KERNEL PRINCIPAL COMPONENT ANALYSISMd. Ashad Alam, Kenji FukumizuIn kernel methods, choosing a suitable kernel is indispensable for favorable results. No well-founded methods, however, have been established in general for unsupervised learning. We focus on kernel Principal Component Analysis (kernel PCA), which is a nonlinear extension of principal component analysis and has been used electively for extracting nonlinear features and reducing dimensionality. As a kernel method, kernel PCA … …Journal of Computer Science, Vol. 10, Issue 7 · 15 Feb 2014 · 8,721 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFORECASTING THE FINANCIAL RETURNS FOR USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSISNop SopipanThe aim of this study was to forecast the returns for the Stock Exchange of Thailand (SET) Index by adding some explanatory variables and stationary Autoregressive order p (AR (p)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Results showed that the multiple regressions based on PCA, … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 17 Apr 2013 · 6,958 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFORECASTING RETURNS FOR THE STOCK EXCHANGE OF THAILAND INDEX USING MULTIPLE REGRESSION BASED ON PRINCIPAL COMPONENT ANALYSISNop Sopipan, Anchalee Sattayatham, Samruam ChongcharoenThe aim of this study was to forecast the returns for the Stock Exchange of Thailand (SET) Index by adding some explanatory variables and stationary Autoregressive Moving-Average order p and q (ARMA (p, q)) in the mean equation of returns. In addition, we used Principal Component Analysis (PCA) to remove possible complications caused by multicollinearity. Afterwards, we forecast the volatility … …Journal of Mathematics and Statistics, Vol. 9, Issue 1 · 18 Mar 2013 · 7,438 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePrincipal Component Analysis Based Feature Extraction, Morphological Edge Detection and Localization for Fast Iris RecognitionM. Suganthy, P. RamamoorthyThis study involves the Iris Localization based on morphological or set theory which is well in shape detection. Principal Component Analysis (PCA) is used for preprocessing, in which the removal of redundant and unwanted data is done. Applications such as Median Filtering and Adaptive thresholding are used for handling the variations in lighting and noise. Features are extracted using Wavelet … …Journal of Computer Science, Vol. 8, Issue 9 · 9 Aug 2012 · 7,748 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFace Biometrics Based on Principal Component Analysis and Linear Discriminant AnalysisLih-Heng Chan, Sh-Hussain Salleh, Chee-Ming TingProblem statement: In facial biometrics, face features are used as the required human traits for automatic recognition. Feature extracted from face images are significant for face biometrics system performance. Approach: In this thesis, a framework of facial biometric was designed based on two subspace methods i.e., Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). First, PCA is used for … …Journal of Computer Science, Vol. 6, Issue 7 · 31 Jul 2010 · 7,664 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleFactors Influencing Online Shopping in Mauritius: An Application of Principal Component Analysis and Binary Logistic RegressionP. Ramtohul, N. Mamode Khan, M. HosenallyIn our modern world, the intensive use of internet has imposed new lifestyles and encouraged new behaviour amongst many across the globe. With the development in Internet technologies, the emergence of online shopping has altered the way businesses operate. While many of them have embraced this platform to present their offerings, many customers on the other hand, are finding it … …Journal of Social Sciences, Vol. 10, Issue 4 · 29 Jan 2015 · 7,698 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleQuality Monitoring Using Principal Component Analysis and Fuzzy Logic Application in Continuous Casting ProcessSalah Bouhouche, Malek Lahreche, Abdelkrim Moussaoui, Jürgen BastThis paper deals with non linear system monitoring, based on a combined use of Principal Components Analysis (PCA) and fuzzy logic to process and quality monitoring. PCA coupled to fuzzy logic was used to estimate the fault or defect according to the dynamic changes in the process inputs-outputs characterized by T2 Hoteling and Squared Prediction Error (SPE). Correlation between the … …American Journal of Applied Sciences, Vol. 4, Issue 9 · 30 Sep 2007 · 7,238 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePrincipal Component Analysis of the Female Pengging Soloan Duck Based on Morphometric TraitsRini Nur Hayati, Subiharta, Yudi Adinata et al.The Pengging Soloan duck is an emerging indigenous genetic resource from Central Java, Indonesia, recognized for its adaptability and egg-laying potential. However, its phenotypic characterization remains limited compared with established Indonesian duck breeds such as Mojosari, Tegal, and Magelang ducks. This study aimed to characterize 70 adult female Pengging Soloan ducks aged 5 6.5 months using Principal Component Analysis (PCA) … …American Journal of Animal and Veterinary Sciences, Vol. 21, Issue 3 · 10 Sep 2026 · 940 accessesView PDFCite