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Principal Component Analysis for Distributions Observed by Samples in Bayes Spaces
Distributional data have recently become increasingly important for understanding processes in the geosciences, thanks to the establishment of...
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Experimental data-driven model development for ESP failure diagnosis based on the principal component analysis
The reliable diagnosis of electrical submersible pump (ESP) failure is a vital process for establishing of the optimal production strategies and...
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Forecasting Surface Facilities Investment Based on Factor Analysis and Multiple Regression Analysis
Surface facilities investment is a critical component of engineering investment estimation, which holds a relatively significant proportion of the...
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Rock Slope Stability Analysis Incorporating the Effects of Intermediate Principal Stress
This paper proposes an analytical approach for assessing rock slope stability based on a three-dimensional (3D) Hoek–Brown (HB) criterion to consider...
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Analysis of climate change in the middle reaches of the Yangtze River Basin using principal component analysis
Global warming and associated frequent extreme hydrological events with increasingly severe climate change threaten human life and economic...
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Local and global timeseries proxies using functional principal component analysis: application to history-matching and uncertainty quantification
Accurate surrogate models are essential for the application of computational methods such as Markov chain Monte Carlo (McMC) using numerical...
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Improved Treatment of Model Prediction Uncertainty: Estimating Rainfall using Discrete Wavelet Transform and Principal Component Analysis
It is necessary to select appropriate rainfall series as input to the hydrologic model to access more accurate hydrologic predictions and estimate...
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Development of a Water Quality Index Using Sparse Principal Component Analysis for the Tigris River in Iraq
AbstractFreshwater levels in the Tigris River significantly reduced during the last two decades due to global warming and geopolitics issues around...
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Reduction of non-tidal oceanographic fluctuations in ocean-bottom pressure records of DONET using principal component analysis to enhance transient tectonic detectability
Ocean bottom pressure-gauge (OBP) records play an essential role in seafloor geodesy. Oceanographic fluctuations in OBP data, however, pose as a...
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A simplified vector valued PSHA using principal components for seismic slope displacement hazard estimation
This study proposes a new seismic slope displacement prediction equation based on uncorrelated principal components and implementation in landslide...
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Integration of ASTER and Soil Survey Data by Principal Components Analysis and One-Class Support Vector Machine for Mineral Prospectivity Map** in Kerkasha, Southwestern Eritrea
This study evaluates the potential for mineral prospectivity map** (MPM) within the Kerkesha area, southwestern Eritrea, using remote sensing and...
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Application of Principal Component Analysis (PCA) to the Evaluation and Screening of Multiactivity Fungi
Continued innovation in screening methodologies remains important for the discovery of high-quality multiactive fungi, which have been of great...
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Watershed Prioritization in Lower Shivaliks Region of India Using Integrated Principal Component and Hierarchical Cluster Analysis Techniques: A Case of Upper Ghaggar Watershed
The watershed prioritization of soil erosion-affected areas is an utmost requirement to formulate management and conservation practices. In this...
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Automatic lithology modelling of coal beds using the joint interpretation of principal component analysis (PCA) and continuous wavelet transform (CWT)
Identification of thin interbedded non-coal bands and coal seams with varying carbon contents within a coal seam is of paramount interest in coal...
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How are various natural disasters cognitively represented?: a psychometric study of natural disaster risk perception applying three-mode principal component analysis
This study explores the features and structure of laypeople’s risk perceptions of natural disasters using a psychometric paradigm (PP) that employs...
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Estimation of Winter Wheat Yield Using the Principal Component Analysis Based on the Integration of Satellite and Ground Information
AbstractThe results of the principal component analysis application for estimating the average regional winter wheat yield based on the integration...
