Principal component analysis of the main factors of line intensity enhancements observed in oscillating direct current plasma

2010 ◽  
Vol 65 (11) ◽  
pp. 927-934 ◽  
Author(s):  
Milovan M. Stoiljković ◽  
Igor A. Pašti ◽  
Miloš D. Momčilović ◽  
Jelena J. Savović ◽  
Mirjana S. Pavlović
Keyword(s):  
Principal Component Analysis ◽  
Direct Current ◽  
Line Intensity ◽  
Principal Component ◽  
Component Analysis ◽  
Direct Current Plasma ◽  
Main Factors

Study on Prediction Model of Grain Yield Based on Principal Component Analysis and BP Neural Network

2015 ◽  
Vol 713-715 ◽  
pp. 1939-1942
Author(s):  
Xing Mei Xu ◽  
Li Ying Cao ◽  
Jing Zhou
Keyword(s):  
Neural Network ◽  
Principal Component Analysis ◽  
Prediction Model ◽  
Grain Yield ◽  
Bp Neural Network ◽  
Principal Component ◽  
Component Analysis ◽  
Jilin Province ◽  
Average Error ◽  
Main Factors

Taking the grain yield data from 1980 to 2012 of Jilin Province for example, this paper analyzes the main factors that influences the grain yield based on the principle component analysis method. According to these main factors, the input samples of BP neutral network are definite. Thereby, the BP neutral networks could be trained to predict. The results show that the fertilizer consumption, large cattle head number, end grain sowing area, effective irrigation area and rural per capita living space are the main effect factor on grain yield. The BP neural network was built by using it as the input samples. The number of input nodes of the network is determined. Then build the prediction model of grain production in Jilin province. The simulation results show that, the average error of prediction results of BP neural network model based on principal component analysis is 4.48%.

scholarly journals Instrumental and Sensory Analysis of the Properties of Traditional Chinese Fried Fritters

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Daming Fan ◽  
Bowen Yan ◽  
Huizhang Lian ◽  
Jianxin Zhao ◽  
Hao Zhang
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Factors Influencing ◽  
Human Evaluation ◽  
Main Factors ◽  
Instrumental Methods ◽  
The Relationship ◽  
Evaluation Techniques

The quality of traditional Chinese fried fritters is typically measured using human sensory evaluation techniques and physicochemical indices, the process of which is laborious and time-consuming. This study aimed to investigate the relationship between instrumental parameters, sensory criteria, and physicochemical indices. Significant correlations were found using principle component analysis. 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.

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

A Principal Component Analysis of Main Factors Influencing Seed Germination of Bioenergy Grass

2013 ◽  
Vol 805-806 ◽  
pp. 236-239
Author(s):  
Dan Shan ◽  
Yan Ping Liu ◽  
En De Xing ◽  
Peng Cheng Gao
Keyword(s):  
Principal Component Analysis ◽  
Seed Germination ◽  
Alternative Energy ◽  
Hot Spot ◽  
Principal Component ◽  
Component Analysis ◽  
Seed Vigor ◽  
Biomass Energy ◽  
Factors Influencing ◽  
Main Factors

Biomass energy is considered to be an ideal renewable alternative energy and herbaceous energy plants as an important biomass resources became research hot spot all over the world. Switchgrass (Panicum virgatum L.) is international recognized as the most suitable bioenergy plant for the past few years. In order to obtain the basic data about seed germination characteristics on switchgrass as a bioenergy grass, different temperatures are investigated to select reliability indexes on seed germination of two species switchgrass from eight measurement indexes and then analyzed main factors influencing seed vigor by a principal component analysis. The result showed that co-efficiency of germination (CG), germination index (GI) and Peak value (PV) from eight germination indexes can be used as measurement indexes for detect seed germination of two species switchgrass.

A German version of the Intermittent Claudication Questionnaire (ICQ): cultural adaptation and validation

VASA ◽  
2012 ◽  
Vol 41 (5) ◽  
pp. 333-342 ◽  
Author(s):  
Kirchberger ◽  
Finger ◽  
Müller-Bühl
Keyword(s):  
Principal Component Analysis ◽  
Intermittent Claudication ◽  
Completion Time ◽  
Short Form ◽  
Principal Component ◽  
Component Analysis ◽  
German Version ◽  
Average Completion Time ◽  
Sf 36 ◽  
Related Quality

Background: The Intermittent Claudication Questionnaire (ICQ) is a short questionnaire for the assessment of health-related quality of life (HRQOL) in patients with intermittent claudication (IC). The objective of this study was to translate the ICQ into German and to investigate the psychometric properties of the German ICQ version in patients with IC. Patients and methods: The original English version was translated using a forward-backward method. The resulting German version was reviewed by the author of the original version and an experienced clinician. Finally, it was tested for clarity with 5 German patients with IC. A sample of 81 patients were administered the German ICQ. The sample consisted of 58.0 % male patients with a median age of 71 years and a median IC duration of 36 months. Test of feasibility included completeness of questionnaires, completion time, and ratings of clarity, length and relevance. Reliability was assessed through a retest in 13 patients at 14 days, and analysis of Cronbach’s alpha for internal consistency. Construct validity was investigated using principal component analysis. Concurrent validity was assessed by correlating the ICQ scores with the Short Form 36 Health Survey (SF-36) as well as clinical measures. Results: The ICQ was completely filled in by 73 subjects (90.1 %) with an average completion time of 6.3 minutes. Cronbach’s alpha coefficient reached 0.75. Intra-class correlation for test-retest reliability was r = 0.88. Principal component analysis resulted in a 3 factor solution. The first factor explained 51.5 of the total variation and all items had loadings of at least 0.65 on it. The ICQ was significantly associated with the SF-36 and treadmill-walking distances whereas no association was found for resting ABPI. Conclusions: The German version of the ICQ demonstrated good feasibility, satisfactory reliability and good validity. Responsiveness should be investigated in further validation studies.

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