Results 11 to 20 of about 408,145 (290)

PCA of PCA: principal component analysis of partial covering absorption in NGC 1365 [PDF]

Monthly Notices of the Royal Astronomical Society, 2014
We analyse 400 ks of XMM-Newton data on the active galactic nucleus NGC 1365 using principal component analysis (PCA) to identify model independent spectral components. We find two significant components and demonstrate that they are qualitatively different from those found in MCG?6-30-15 using the same method.
Parker, M. L., Walton, D. J., Fabian, A. C., RISALITI, GUIDO   +3 more
openaire   +7 more sources

Sparse logistic principal components analysis for binary data [PDF]

, 2010
We develop a new principal components analysis (PCA) type dimension reduction method for binary data. Different from the standard PCA which is defined on the observed data, the proposed PCA is defined on the logit transform of the success probabilities ...
Hu, Jianhua, Huang, Jianhua Z., Lee, Seokho   +2 more
core   +3 more sources

Optimized Principal Component Analysis on Coronagraphic Images of the Fomalhaut System [PDF]

, 2013
We present the results of a study to optimize the principal component analysis (PCA) algorithm for planet detection, a new algorithm complementing ADI and LOCI for increasing the contrast achievable next to a bright star.
Amara, A., Kenworthy, M., Meshkat, T., Quanz, S. P.   +3 more
core   +3 more sources

Principal Component Analysis (PCA)-Supported Underfrequency Load Shedding Algorithm [PDF]

Energies, 2020
This research represents a conceptual shift in the process of introducing flexibility into power system frequency stability-related protection. The existing underfrequency load shedding (UFLS) solution, although robust and fast, has often proved to be incapable of adjusting to different operating conditions.
Tadej Skrjanc, Rafael Mihalic, Urban Rudez   +2 more
openaire   +3 more sources

Integrating Neutrosophic Logic into Principal Component Analysis: A Python-Based Framework [PDF]

Neutrosophic Sets and Systems
Principal Component Analysis (PCA) is a widely used dimensionality reduction technique that transforms correlated variables into a smaller set of uncorrelated principal components. However, classical PCA assumes precise and crisp data, which may not hold
D. Vidhya, S. Jafari, G. Nordo
doaj   +1 more source

Representing complex data using localized principal components with application to astronomical data [PDF]

, 2007
Often the relation between the variables constituting a multivariate data space might be characterized by one or more of the terms: ``nonlinear'', ``branched'', ``disconnected'', ``bended'', ``curved'', ``heterogeneous'', or, more general, ``complex ...
A Gersho, A Gorban, AH Monaghan, AR Webb, B Chalmond, B Kégl, C Allende Prieto, CAL Bailer-Jones, CAL Bailer-Jones, DJ Marchette, E Diday, E Oja, EC Malthouse, EM Braverman, FL Hall, H Hotelling, H Späth, H Wold, IT Jolliffe, J Einbeck, J Einbeck, JH Friedman, JH Friedman, JH Friedman, JJ Verbeek, JM Chambers, K Fukunaga, K Hornik, L Breiman, MAC Perryman, MG Kendall, N Kambhatla, P Delicado, P Delicado, PG Willemsen, R Tibshirani, RJ Bolton, S de Jong, T Aluja-Banet, T Duchamps, T Hastie, T Hastie, WS Cleveland, Z-Y Liu   +43 more
core   +1 more source

Application of PCA-LSTM algorithm for financial market stock return prediction and optimization model

International Journal for Simulation and Multidisciplinary Design Optimization, 2023
Accurately predicting stock returns can help reduce market risk. This paper briefly introduced the long short-term memory (LSTM) algorithm model for predicting stock returns and combined it with principal component analysis (PCA) to improve the ...
Mi Yanxiang, Xu Donghai, Gao Tielin
doaj   +1 more source

Assessing the spatiotemporal dynamics of maize yield in the central and northern regions of Ukraine

Agrology, 2019
This paper aims to establish the regularities of the spatio-temporal variability of maize yield in the Polissya and Forest-steppe zones of Ukraine, identify the factors that have the greatest impact on the yield of maize and to carry out zoning of the ...
A. A. Zymaroieva, T. P. Fedonyuk
doaj   +1 more source

Principal component analysis of texture features derived from FDG PET images of melanoma lesions

EJNMMI Physics, 2022
Background The clinical utility of radiomics is hampered by a high correlation between the large number of features analysed which may result in the “bouncing beta” phenomenon which could in part explain why in a similar patient population texture ...
DeLeu Anne-Leen, Sathekge Machaba, Maes Alex, De Spiegeleer Bart, Beels Laurence, Sathekge Mike, Pottel Hans, Christophe Van de Wiele   +7 more
doaj   +1 more source

Volatiles Distinguishing the European ‘Conference’ and the Asian ‘Yali’ Pears Stored at Different Post-Harvest Temperatures

Horticulturae, 2022
A total of 124 identical volatile aromatic compounds were identified during storage of the European ‘Conference’ and the Asian ‘Yali’ pear cultivars in different temperature conditions. Only 5 volatiles were statistically differentiated in both cultivars
Jan Goliáš, Josef Balík, Jiří Létal   +2 more
doaj   +1 more source