The Principal Component Analysis of Coastal Areas

2014 ◽  
Vol 513-517 ◽  
pp. 3703-3706
Author(s):  
Qiu Ju Wang ◽  
Da Shen Xue
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Coastal Areas ◽  
Principal Component Analysis Analysis ◽  
Consumer Prices ◽  
The Government ◽  
Main Component ◽  
The Impact

In order to development the economic of China's coastal areas better, the paper mainly discusses the coastal areas of China's consumer price factors, the main use of software SPSS, using statistical analysis, principal component analysis, analysis that the impact is the main component of consumer prices and reached the level of consumer prices in coastal areas, which is conducive to the Government to take appropriate measures to faster and better development of the region's economy.

scholarly journals Chemical Composition and Variability of Leaf and Berry oils from Corsican Juniperus macrocarpa

2018 ◽  
Vol 13 (2) ◽  
pp. 1934578X1801300
Author(s):  
Joséphine Ottavioli ◽  
Ange Bighelli ◽  
Joseph Casanova ◽  
Félix Tomi
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Chemical Composition ◽  
Principal Component ◽  
Component Analysis ◽  
Germacrene D ◽  
Leaf Oil ◽  
Main Components ◽  
Main Component ◽  
C Nmr

The chemical composition of five leaf oil samples and eighteen berry oil samples from Corsican Juniperus macrocarpa have been investigated by GC(RI), GC-MS and 13C NMR. The composition of berry oils was dominated by monoterpene hydrocarbons with α-pinene (56.4-78.9%) as main component followed by myrcene (2.2-11.9%). Germacrene D (4.5-103%) was the major sesquiterpene. The contents of the main components of leaf oils varied drastically from sample to sample: α-pinene (28.7-76.4%), δ3-carene (up to 17.3%), β-phellandrene (up to 12.3%), manoyl oxide (up to 8.1%). The occurrence of the unusual ( Z)-pentadec-6-en-2-one (0.1-1.2%) should be pointed out. Statistical analysis (Principal Component Analysis and k- means partition) suggested a unique group with atypical samples.

The Correction Model of Webster Method for Intersection Delay

2011 ◽  
Vol 97-98 ◽  
pp. 503-506
Author(s):  
Han Bai ◽  
Kai Deng ◽  
Nan Wang ◽  
Qiang Qiang Qiao
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Traffic Control ◽  
Principal Component ◽  
Component Analysis ◽  
Impact Factors ◽  
Important Indicator ◽  
Correction Model ◽  
The Impact

Intersection delay, an important indicator of traffic control, is often calculated by the Webster formula nowadays. This study investigated and analyzed the delay of several intersections in Jinan using the principal component analysis to identify the impact factors of the delay. Statistical analysis was used by MATLAB to build the correction model of Webster formula for intersection delay.

scholarly journals Economic Causes of Extremism Intellectual (Thoughts) Views of Graduate Students Using Multivariate Statistical Techniques

2016 ◽  
Vol 9 (7) ◽  
pp. 160
Author(s):  
Hasan Abdullah Al-Dajah
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Statistical Analysis ◽  
Graduate Students ◽  
Multivariate Statistical Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Multivariate Statistical ◽  
The Impact

The present study investigated the impact of the economic reasons on the intellectual (thoughts) extremism, and the statement of the most important indicators in the economic factor that lead to extremism from the views of graduate students. The study problem based on the following question: What are economic factors leading to the extremism of the intellectual(Thoughts)? Correlation coefficient, Principal component analysis (PCA), varimax (F) rotated factor analysis, and dendrogram cluster analysis (DCA) were assessed for the economic impacts that leads to extremism(Thoughts). Multivariate statistical analysis of the dataset and correlation analysis suggested that the strong positive correlations are commonly associated in the poverty and lack of interest in remote areas for major cities Center. Multivariate statistical analysis such as principal component analysis, varimax rotated factor analysis, and dendrogram cluster analysis allowed the identification of three main factors controlling that lead to extremism from the views of graduate students. The extracted factors are as follows: low living expenses, poverty and substantial deprivation, and unequal opportunities and unemployment associations related to prevalence of corruption phase.

Evaluation of the Aging Behavior of High Density Polyethylene in Thermal Oxidative Environment by Principal Component Analysis

2017 ◽  
Vol 727 ◽  
pp. 447-449 ◽  
Author(s):  
Jun Dai ◽  
Hua Yan ◽  
Jian Jian Yang ◽  
Jun Jun Guo
Keyword(s):  
Principal Component Analysis ◽  
Impact Strength ◽  
High Density Polyethylene ◽  
Tensile Modulus ◽  
Principal Component ◽  
Component Analysis ◽  
High Density ◽  
Aging Behavior ◽  
Data Set ◽  
The Impact

To evaluate the aging behavior of high density polyethylene (HDPE) under an artificial accelerated environment, principal component analysis (PCA) was used to establish a non-dimensional expression Z from a data set of multiple degradation parameters of HDPE. In this study, HDPE samples were exposed to the accelerated thermal oxidative environment for different time intervals up to 64 days. The results showed that the combined evaluating parameter Z was characterized by three-stage changes. The combined evaluating parameter Z increased quickly in the first 16 days of exposure and then leveled off. After 40 days, it began to increase again. Among the 10 degradation parameters, branching degree, carbonyl index and hydroxyl index are strongly associated. The tensile modulus is highly correlated with the impact strength. The tensile strength, tensile modulus and impact strength are negatively correlated with the crystallinity.

scholarly journals Principal component analysis implementation for brainwave signal reduction based on cognitive activity

2017 ◽  
Vol 3 (3) ◽  
pp. 125 ◽  
Author(s):  
Ahmad Azhari ◽  
Murein Miksa Mardhia
Keyword(s):  
Principal Component Analysis ◽  
Cognitive Task ◽  
Cognitive Activity ◽  
Electrical Potential ◽  
Principal Component ◽  
Component Analysis ◽  
Wave Form ◽  
Brain Response ◽  
Cumulative Rate ◽  
Main Component

Human has the ability to think that comes from the brain. Electrical signals generated by brain and represented in wave form.  To record and measure the activity of brainwaves in the form of electrical potential required electroencephalogram (EEG). In this study a cognitive task is applied to trigger a specific human brain response arising from the cognitive aspect.  Stimulation is given by using nine types of cognitive tasks including breath, color, face, finger, math, object, password thinking, singing, and sports. Principal component analysis (PCA) is implemented as a first step to reduce data and to get the main component of feature extraction results obtained from EEG acquisition. The results show that PCA succeeded reducing 108 existing datasets to 2 prominent factors with a cumulative rate of 65.7%. Factor 1 (F1) includes mean, standard deviation, and entropy, while factor 2 (F2) includes skewness and kurtosis.

scholarly journals Statistical Analysis of Mitochondrial Pathologies in Childhood: Identification of Deficiencies Using Principal Component Analysis

2000 ◽  
Vol 80 (7) ◽  
pp. 1019-1030 ◽  
Author(s):  
Thierry Letellier ◽  
Gilles Durrieu ◽  
Monique Malgat ◽  
Rodrigue Rossignol ◽  
Jaromir Antoch ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Principal Component ◽  
Component Analysis

scholarly journals Principal Component Analysis of Multiwavelength Properties of Seyfert Galaxies

1994 ◽  
Vol 159 ◽  
pp. 502-502
Author(s):  
Deborah Dultzin–Hacyan ◽  
Carlos Ruano
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Principal Component ◽  
Seyfert Galaxies ◽  
Component Analysis ◽  
X Ray ◽  
Radio Data

A multidimensional statistical analysis of observed properties of Seyfert galaxies has been carried out using Principal Component Analysis (PCA) applied to X-ray, optical, near and far IR and radio data for all the Seyfert galaxies types 1 and 2 for the catalog by Lipovtsky et al. (1987).

scholarly journals Statistical Study of Variability in Rainfall and Analysis of Etreme Rainfall Events for Hill Stations of Uttarakhand

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Bimal Pande ◽  
Sneh Joshi ◽  
Seema Pande
Keyword(s):  
Principal Component Analysis ◽  
Statistical Analysis ◽  
Statistical Study ◽  
Parametric Method ◽  
Principal Component ◽  
Extreme Rainfall ◽  
Component Analysis ◽  
Rainfall Pattern ◽  
Composite Matrix ◽  
Rainfall Events

Statistical analysis of rainfall pattern and its variability for 20 years (1990-2010) data is performed for two mountainous urban centres of Uttarakhand i.e. Almora (29.60 N, 79.670 E and altitude 1,204m asl) and Nainital (29.40 N, 79.470 E and altitude 2,020m asl). Non Parametric method of Principal Component Analysis (PCA) gives the correlation between different extreme rainfall indices. It is concluded that PCA suggest 90% of the variance in composite matrix of extreme rainfall indices.

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