Fault early warning model of 4G base station out of service based on centralized monitoring data resources by Yang WANG, Yi MAN, Zhipeng CHEN

“…4G wireless base station equipment is an important link which has direct impact on information communication network customer service quality,and 4G wireless base stations out of service fault will directly block users' normal communication.Aiming at these problems,based on the centralized monitoring warning message data resources through association rule mining and time trace deduction analysis,4G base stations out of service fault short-term warning was achieved.Based on centralized monitoring equipment performance data resources,by the classification of network elements (data cleaning,feature selection,network elements clustering),index dimension reduction (grouped by cluster,principal component analysis),principal component expression and out of service fault correlation analysis,performance indicators selection and threshold analysis,4G base stations out of service fault long-term warning was achieved.The test can accurately predict the 27.8% of 4G base station equipment out of service fault next month.…”
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Psychometric Properties of the Moore Index of Nutrition Self-Care in Arabic: A Study among Saudi Adolescents at King Saud University, Riyadh, Saudi Arabia by Adel Bashatah, Khalid A. Alahmary

“…The construct validity was examined through principal component analysis. Results. The MIN-SC instrument was shown to be internally consistent with reliable scoring (Cronbach’s alpha = 0.910). …”
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Diabetes Risk Assessment: A Comparative Study of Decision Trees and Ensemble Learning Models by Lei Tianxing

“…The study’s experimental results demonstrate that applying Principal Component Analysis (PCA) to preprocess the data, followed by training a Random Forest (RF) model with 80% of the dataset, achieves an impressive accuracy of 89.86%. …”
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Instrumental and Sensory Analysis of the Properties of Traditional Chinese Fried Fritters by Daming Fan, Bowen Yan, Huizhang Lian, Jianxin Zhao, Hao Zhang

“…Volume, fat, texture, palatability, and instrumental parameters (hardness, fracturability, springiness, and gumminess) were found to be the main factors influencing the quality of Chinese fried fritters by principal component analysis (PCA) and instrumental methods, which were satisfactory replacement for human evaluation in correlation testing.…”
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Feature Frequency Extraction Algorithm based on PCA and MK-MOMEDA and Its Application by Jiawei Zheng, Qihong Liu, Weiguang Li, Xuezhi Zhao, Guochen Li

“…Aiming at the problem of extracting characteristic frequency of flexible thin-walled bearings，a feature frequency extraction algorithm combining principal component analysis （PCA） and multi-point optimally adjusted minimum entropy deconvolution （MOMEDA） is proposed. …”
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Study of Selected Metals Distribution, Source Apportionment, and Risk Assessment in Suburban Soil, Pakistan by Javed Iqbal, Munir H. Shah

“…Substantial human inputs for Cd, Co, Cr, Cu, Mn, Pb, Sr, and Zn were also revealed by principal component analysis in the examined soil. Overall the study area was found to be contaminated at considerable/high degree.…”
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Variation of Water Quality in Ningxia Section of the Yellow River in Recent 5 Years by Yan Jin, Xinyuan Wang, Ya-Ping Dong

“…Both the Nemerow index method and the contamination degree method showed that total nitrogen with high concentration exerted the water pollution. Principal component analysis also proved this. Stricter environmental management strategies for controlling total nitrogen should be taken in the future. …”
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Investigation and Discrimination of Ballpoint Pen Inks by Analytical Techniques and Chemometrics by Mehwish Sharif, Sohail Chand, Syed Azhar Ali Shah Tirmazi, Umar Farooq, Muhammad Makshoof Athar, Madeeha Batool

“…The statistical techniques of principal component analysis and cluster analysis have been applied on obtained data. …”
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Reduction of Multidimensional Image Characteristics Based on Improved KICA by Jia Dongyao, Ai Yanke, Zou Shengxiong

“…Dimensionality reduction and optimization of characteristic parameter model based on improved kernel independent component analysis are proposed in this paper; the independent primitives are obtained by KICA (kernel independent component analysis) algorithm to construct an independent group subspace, while using 2DPCA (2D principal component analysis) algorithm to complete the second order related to data and further reduce the dimension in the above method. …”
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Temperature Variability over the Po Valley, Italy, according to Radiosounding Data by Boyan Hristozov Petkov

“…Temperature variations registered above the southeast part of the Po Valley, Italy, have been examined by applying the principal component analysis of radiosounding profiles recorded during the period from 1987 to 2010. …”
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The Study for Saving Energy and Optimization of LED Street Light Heat Sink Design by Chi-Chang Hsieh, Yan-Huei Li

“…The study employed the Taguchi method for experiment planning and used gray relational analysis and principal component analysis to determine the optimal parameter combination for cooling fins. …”
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An Analysis of the Economic Impact of US Presidential Elections Based on Principal Component and Logical Regression by Jing-Jing Wang, Yan Liang, Jin-Tao Su, Jia-Ming Zhu

“…In order to investigate the impact of the US presidential election on the economy, this paper first constructs an analysis model of the economic impact on the United States based on stepwise regression and principal component analysis to analyze the focus of different candidates’ attention on the economic issues and its possible impact on the US economy in the election year and after the election; secondly, a Chinese economic impact analysis model based on factor analysis and machine learning logistic regression was constructed to analyze the impact of the US presidential election on the Chinese economy. …”
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Evaluation and Numerical Simulation of Music Education Informationization Based on the Local Linear Regression Method by Jiping Liu

“…The choice of different weights is subjected to principal component analysis. The evaluation of music education informatization level mainly evaluates the status quo of music education informatization development, provides a basis for formulating and adjusting music education informatization development policies, and provides support for educational decision-making, to promote the sustainable and balanced development of music education informatization. …”
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Air quality investigation using functional data analysis methods by Akvilė Vitkauskaitė, Milda Salytė

“…The analysis employs data smoothing, principal component analysis (PCA), exploratory data analysis, hypothesis testing, and time series analysis to provide a thorough examination. …”
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Cladistics with geometric morphometric data: The variability of the calvarium in the genus Homo by Margaux Simon-Maciejewski, Giorgio Manzi, Valéry Zeitoun, Aurélien Mounier

“…The first protocol used the coordinates of the principal components, obtained after a principal component analysis, as variables describing the OTUs. …”
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Fresh sweet cherry fruit characterization and differentiation by Raman spectroscopy coupled with PCA by Volić Mina, Obradović Nataša, Milošević Nebojša, Pećinar Ilinka

“…By combining Raman spectroscopy with principal component analysis (PCA), samples nutritionally similar to studied cherry cultivars can be distinguished.…”
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The Feasibility Study for Multigeometries Identification of Uranium Components Using PCA-LSSVM Based on Correlation Measurements by Mi Zhou, Peng Feng, Yixin Liu, Biao Wei

“…In this paper, we proposed an identification method combining principal component analysis and least-square support vector machine (PCA-LSSVM). …”
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Application research on the time–frequency analysis method in the quality detection of ultrasonic wire bonding by Wuwei Feng, Xin Chen, Cuizhu Wang, Yuzhou Shi

“…Then, the principal component analysis method was further used for feature selection. …”
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Application of Combined Multiple Linear Regression Model in Runoff Prediction by GUO Cunwen

“…In order to improve the hydrological prediction accuracy,a shuffled frog leaping algorithm (SFLA)-combined multiple linear regression (CMLR) runoff prediction model is proposed.This paper first builds a CMLR model based on principal component analysis (PCA) data with and without dimensionality reduction;then optimizes the CMLR constant term,partial regression coefficient and combined weight coefficient by the SFLA to establish a SFLA-CMLR runoff prediction model;finally apply the SFLA-CMLR model on two examples of annual runoff prediction,and establishes the SFLA-PCA-MLR,SFLA-PCA-SVM (support vector machine),(least squares) LS-PCA-MLR,PCA-SVM,with dimensionality reduction of PCA,as well as SFLA-MLR,SFLA-SVM,LS-MLR,SVM,without dimensionality reduction as comparative prediction models.The results show that the average relative error of the SFLA-CMLR model for the annual runoff prediction of the two examples is 1.54% and 4.63%,respectively,and the prediction accuracy is better than that of SFLA-PCA-MLR and other 8 models.Therefore,it has better prediction accuracy and generalization ability.…”
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Trend Analysis of Pakistan Railways Based on Industry Life Cycle Theory by Li Xuemei, Khalid Mehmood Alam, Shitong Wang

“…The core purpose of this paper was to analyze the trend analysis of Pakistan railways from the year 1950 to 2015, using the principal component analysis method and industrial life cycle theory. …”
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