Application of Principal Component Analysis for Steel Material Components by Miran Othman Tofiq, Kawa Muhammad Jamal Rasheed

Subjects: “…Principal Component Analysis (PCA)…”
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Principal component analysis of time delay in large IP network by Xuan WEI, Xiaoying HUANG

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New Role of Thermal Mapping in Winter Maintenance with Principal Components Analysis by Mario Marchetti, Lee Chapman, Abderrahmen Khalifa, Michel Buès

“…This work investigates the role of statistics in adding value to thermal mapping data. Principal components analysis is used to interpolate between individual thermal mapping surveys to build a thermal map (or even a road surface temperature forecast), for a wider range of climatic conditions than that permitted by traditional surveys. …”
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Labor Market Resource Allocation Optimization Based on Principal Component Analysis by Xiaojing Liu

“…Secondly, the principal component analysis is used to calculate the weights of indicators such as market share, industrial growth rate, employment contribution rate, and the pulling ability to GDP, and then the strength of each industry is calculated. …”
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Research on indoor localization algorithm based on kernel principal component analysis by Hua-liang LI, Zhi-hong QIAN, Hong-liang TIAN

“…An indoor localization algorithm based on kernel principal component analysis (KPCA) was proposed.It applied KPCA to train the original location fingerprint (OLF) and extract the nonlinear feature of the OLF data at the offline stage,such that the information of all AP was more efficiently utilized.At the online stage,an improved weight k-nearest neighbor algorithm for positioning which could automatically choose neighbors was proposed.The experiments were carried out in a realistic WLAN environment.The results show that the algorithm outperforms the existing methods in terms of the mean error and localization accuracy.Moreover,it requires less times of RSS acquisition and AP number.…”
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Application of Principal Component Analysis as a Prediction Model for Feline Sporotrichosis by Franco Bresolin Pegoraro, Rita Maria Venâncio Mangrich-Rocha, Saulo Henrique Weber, Marconi Rodrigues de Farias, Elizabeth Moreira dos Santos Schmidt

“…The higher occurrence in male cats in this study could be related to being non-neutered and having access to open spaces. Principal component analysis (PCA) with two principal components, followed by binary logistic regression, and binary logistic regression analysis, with independent variables and backward elimination modeling, were performed to evaluate hematological (n = 56) and biochemical (n = 34) analytes, including red blood cells, hemoglobin, hematocrit, leukocytes, segmented neutrophils, band neutrophils, eosinophils, lymphocytes, monocytes, total plasma protein, albumin, urea, creatinine, and alanine aminotransferase. …”
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Dynamic generalized principal component analysis with applications to fault subspace modeling by Xiaofeng FENG, Jianfeng XU, Chuan HE

Subjects: “…dynamic generalized principal component analysis…”
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Raman Microspectral Study and Classification of the Pathological Evolution of Breast Cancer Using Both Principal Component Analysis-Linear Discriminant Analysis and Principal Component Analysis-Support Vector Machine by Heping Li, Yu Ren, Fan Yu, Dongliang Song, Lizhe Zhu, Shibo Yu, Siyuan Jiang, Shuang Wang

“…To facilitate the enhanced reliability of Raman-based tumor detection and analytical methodologies, an ex vivo Raman spectral investigation was conducted to identify distinct compositional information of healthy (H), ductal carcinoma in situ (DCIS), and invasive ductal carcinoma (IDC). Then, principal component analysis-linear discriminant analysis (PCA-LDA) and principal component analysis-support vector machine (PCA-SVM) models were constructed for distinguishing spectral features among different tissue groups. …”
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PRINCIPAL COMPONENT ANALYSIS (PCA) OF THE ACTIVITIES OF INFORMAL CONSTRUCTION WORKERS/ARTISANS IN NIGERIA by Sunday Julius Odediran, Olubola Babalola

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Fault Diagnosis Method Based on Information Entropy and Relative Principal Component Analysis by Xiaoming Xu, Chenglin Wen

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Rootlets Hierarchical Principal Component Analysis for Revealing Nested Dependencies in Hierarchical Data by Korey P. Wylie, Jason R. Tregellas

“…To address this, the current work describes a novel rootlets hierarchical principal component analysis (hPCA). This method extends typical hPCA using multivariate statistics to construct adaptive multiway mergers and Riemannian geometry to visualize nested dependencies. …”
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Principal component analysis and its generalizations for any type of sequence (PCA-Seq) by V. M. Efimov, K. V. Efimov, V. Y. Kovaleva

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Design and Implementation of an Integrated Network Management System Based on Principal Component Analysis by Xiangyun Kong, Tienan Chu

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Novel adaptive generalized principal component analysis algorithm based on Hebbian rule by Yingbin GAO, Xiangyu KONG, Qiaohua CUI, Haidi DONG

“…In order to adaptively estimate the generalized principal component from input signals,a novel generalized principal component analysis algorithm was proposed based on the Hebbian linear neuron model.Since the autocorrelation matrices of the signals were estimated directly from the sampled data at the current time,the proposed algorithm had low computation complexity.Trough analyzing all of the equilibrium points by Lyapunov method,it is proven that if and only if the weight vector in the neuron had the same direction with the generalized principal component,the proposed algorithm attains the convergence status.Simulation results shows that compared with some same type algorithms,the proposed algorithm has faster convergence speed.…”
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Loss-Aware Histogram Binning and Principal Component Analysis for Customer Fleet Analytics by Kunxiong Ling, Jan Thiele, Thomas Setzer

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Evaluation of Service Life of Polystyrene in Tropical Marine Environment by Principal Component Analysis by Dongdong Song, Jin Gao, Lin Lu, Xiaogang Li

“…To predict the service life of polystyrene (PS) under an aggressive environment, the nondimensional expression Z was established from a data set of multiple properties of PS by principal component analysis (PCA). In this study, PS specimens were exposed to the tropical environment on Xisha Islands in China for two years. …”
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Analytical techniques and software for the study of intragroup metric variation using principal component analysis by Andrej Alexeevich Evteev, Nikolai Evgenievich Staroverov, Nikolai Nikolaevich Potrakhov

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Longitudinal Viral Load Clustering for People With HIV Using Functional Principal Component Analysis by Yunqing Ma, Xueying Yang, Jiayang Xiao, Xiaoming Li, Bankole Olatosi, Jiajia Zhang

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Evaluation of Ecological Water Conservancy Benefits for Lakeside Cities Based on Principal Component Analysis by GU Xiaohan, ZHU Shijie, MAO Jinqiao

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Multielement Principal Component Analysis and Origin Traceability of Rice Based on ICP-MS/MS by Yan Wang, Xiaoxuan Yuan, Linan Liu, Junmei Ma, Sufang Fan, Yan Zhang, Qiang Li

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