Enhancements to a Geographically Weighted Principal Component Analysis in the Context of an Application to an Environmental Data Set

AbstractIn this study, we used bootstrap simulation of a real data set to investigate the impact of sample size (N = 20, 30, 40 and 50) on the eigenvalues and eigenvectors resulting from principal component analysis (PCA). For each sample size, 100 bootstrap samples were drawn from environmental data matrix pertaining to water quality variables (p = 22) of a small data set comprising of 55 samples (stations from where water samples were collected). Because in ecology and environmental sciences the data sets are invariably small owing to high cost of collection and analysis of samples, we restricted our study to relatively small sample sizes. We focused attention on comparison of first 6 eigenvectors and first 10 eigenvalues. Data sets were compared using agglomerative cluster analysis using Ward’s method that does not require any stringent distributional assumptions.

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

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.727.447 ◽

2017 ◽

Vol 727 ◽

pp. 447-449 ◽

Cited By ~ 1

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.

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Application of geographically weighted principal component analysis and fuzzy approach for unsupervised landslide susceptibility mapping on Gish River Basin, India

Geocarto International ◽

10.1080/10106049.2020.1778105 ◽

2020 ◽

pp. 1-24 ◽

Cited By ~ 4

Author(s):

Tirthankar Basu ◽

Arijit Das ◽

Swades Pal

Keyword(s):

Principal Component Analysis ◽

River Basin ◽

Landslide Susceptibility ◽

Principal Component ◽

Component Analysis ◽

Susceptibility Mapping ◽

Landslide Susceptibility Mapping ◽

Fuzzy Approach ◽

Weighted Principal Component

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Optimization of Process Parameters for Submerged Arc Welding by Weighted Principal Component Analysis Based Taguchi Method

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.622-623.45 ◽

2012 ◽

Vol 622-623 ◽

pp. 45-50 ◽

Cited By ~ 1

Author(s):

Joydeep Roy ◽

Bishop D. Barma ◽

J. Deb Barma ◽

S.C. Saha

Keyword(s):

Principal Component Analysis ◽

Taguchi Method ◽

Arc Welding ◽

Principal Component ◽

Traverse Speed ◽

Component Analysis ◽

Submerged Arc Welding ◽

Bead Geometry ◽

Weighted Principal Component ◽

Submerged Arc

In submerged arc welding (SAW), weld quality is greatly affected by the weld parameters such as welding current, traverse speed, arc voltage and stickout since they are closely related to weld joint. The joint quality can be defined in terms of properties such as weld bead geometry and mechanical properties. There are several control parameters which directly or indirectly affect the response parameters. In the present study, an attempt has been made to search an optimal parametric combination, capable of producing desired high quality joint in submerged arc weldment by Taguchi method coupled with weighted principal component analysis. In the present investigation three process variables viz. Wire feed rate (Wf), stick out (So) and traverse speed (Tr) have been considered and the response parameters are hardness, tensile strength (Ts), toughness (IS).

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