Applying principal component analysis and grey relation analysis to analyze the influence factors of quality and safety of dairy products in China

2017 ◽  
Author(s):  
Dafang Li ◽  
Qingchun Wu
Keyword(s):  
Principal Component Analysis ◽  
Dairy Products ◽  
Influence Factors ◽  
Principal Component ◽  
Component Analysis ◽  
Quality And Safety ◽  
Grey Relation Analysis ◽  
Relation Analysis ◽  
Grey Relation

Fuzzy grey relation analysis on torque influence factors of alternating current electrodyna-mometer

2013 ◽  
Vol 26 (8) ◽  
pp. 693-698 ◽  
Author(s):  
Zhigang Zhang ◽  
Guixiang Zhang ◽  
Teng Liu ◽  
Cheng Qian ◽  
Yuanwang Deng
Keyword(s):  
Influence Factors ◽  
Alternating Current ◽  
Grey Relation Analysis ◽  
Relation Analysis ◽  
Grey Relation

Evaluation Study on the Network Impact Index of WeChat Based on Principal Component Analysis

2016 ◽  
Vol 13 (10) ◽  
pp. 7676-7679 ◽  
Author(s):  
Yi Liu
Keyword(s):  
Principal Component Analysis ◽  
Principal Components ◽  
Influence Factors ◽  
Principal Component ◽  
Modern Society ◽  
Component Analysis ◽  
Evaluation Study ◽  
Positive Energy ◽  
Impact Index ◽  
And Function

WeChat software is an important social tool in modern society. This paper discusses the network impact of WeChat from ten aspects including WeChat popularity, attention, video observability, network reputation, function usability, dissemination speed of information, transmission ratio of positive energy and impact of WeChat on network economy, politics and culture, and questionnaires on these ten influence factors are distributed to college students for investigation. Principal component analysis is used to deal with the survey results, the principal components of the ten factors are extracted, and the results show that WeChat popularity, attention, video observability, network reputation and function usability are the main components, in which WeChat popularity, attention and video observability are the factors having the greatest impact on the calculation. And this paper presents the function relationship between the main principal components of WeChat network impact index and these ten influence factors, to evaluate the network impact index of WeChat.

Grey Relation Analysis on the Influence Factors of Multi-Mode Penetrators Forming

2012 ◽  
Vol 538-541 ◽  
pp. 739-743
Author(s):  
Jiang Bo Wang ◽  
Qing Ming Zhang ◽  
Cheng Liang Feng ◽  
Wei Bing Li
Keyword(s):  
Optimization Design ◽  
Influence Factors ◽  
Reference Method ◽  
Shaped Charge ◽  
Grey Relation Analysis ◽  
Height Ratio ◽  
Gray Relation Analysis ◽  
Relation Analysis ◽  
Grey Relation ◽  
Multi Mode

On how to properly choose initiation position and parameters of cavity liner structure of multi-mode penetrator shaping. Combine gray relation analysis with simulation of different ways of initiation and different cavity liner structure, we analyze the effect of ways of initiation, the height of cavity liner, height ratio of cone and thickness of cavity liner on forming parameters of shaped charge. We get the sequence of factors which affect the penetrator molding effect. That is charge initiation position>the height of cavity liner>cone height ratio of cavity liner> thickness of cavity liner, which provide a reference method for optimization design multi-mode warhead.

Grinding Wheel Abrasive in Material Selection Using Fuzzy Grey Relation Analysis Method

2014 ◽  
Vol 1022 ◽  
pp. 18-21 ◽  
Author(s):  
Jian Hua Leng
Keyword(s):  
Material Selection ◽  
Influence Factors ◽  
Selection Problem ◽  
Variation Method ◽  
Grinding Wheel ◽  
Analysis Method ◽  
Grey Relation Analysis ◽  
Abrasive Material ◽  
Relation Analysis ◽  
Grey Relation

Material selection is an important step of product design process. There are often several influence factors in the grinding wheel abrasive material selection problem. This article will put forward a fuzzy grey relation analysis method to the grinding wheel abrasive material selection problem which influences factor (evaluation attribute) values expressed with triangular fuzzy numbers. The Coefficient of variation method will be adopted to determine the evaluation attributes’ weight. Finally, an example is used to analysis the effectiveness and feasibility of the proposed method.

scholarly journals Identification of influence factors on physical-mechanical properties, using the principal component analysis, in selecting the textile fabrics for the clothing products

2020 ◽  
Vol 71 (05) ◽  
pp. 438-445
Author(s):  
Liliana Hristian ◽  
Maria Magdalena Ostafe ◽  
Ionut Dulgheru ◽  
Liliana Buhu ◽  
Adrian Buhu ◽  
...  
Keyword(s):  
Mechanical Properties ◽  
Principal Component Analysis ◽  
Influence Factors ◽  
Principal Component ◽  
Component Analysis ◽  
Woven Fabrics ◽  
Textile Fabrics ◽  
Pca Method ◽  
Main Factors ◽  
Fabric Design

The paper aims to highlight the correlations between the physical-mechanical properties of woven fabrics made of combed wool yarn with different fibrous compositions, using the Principal Component Analysis (PCA) method. Based on the information on each fabric/assortment group, it is found that four main factors were extracted: durability, comfort, production price and fabric design. The extracted components explain 92% of the variability of the twelve initial inter-correlated variables, so that we can considerably reduce the complexity of the data configured using these components, with only 8% loss of information. This technique that follows the controlled reduction of the number of variables can be used subsequently for modelling the physical-mechanical properties of the fabrics and for selecting the most suitable fabrics to satisfy the requirements of a particular field of use

Sign in / Sign up

Export Citation Format

Share Document