A Study on International Competitiveness for Education Service and Influencing Factors in Korea: Focused on the TCI and Grey Analysis Method

2017 ◽  
Vol 13 (5) ◽  
pp. 509-527
Author(s):  
Yao Lu ◽  
◽  
Sung-Joon Lee ◽  
Keyword(s):  
Influencing Factors ◽  
International Competitiveness ◽  
Analysis Method ◽  
Grey Analysis ◽  
Education Service

A novel approach of fault-influencing factors analysis for high-voltage switchgears quality supervision based on industrial big data

2019 ◽  
Vol 233 (14) ◽  
pp. 2531-2546 ◽  
Author(s):  
Xianguang Kong ◽  
Jiantao Chang ◽  
Pei Wang ◽  
Siyi Gong ◽  
Yabin Shi ◽  
...  
Keyword(s):  
Big Data ◽  
Qualitative Analysis ◽  
Influencing Factors ◽  
High Voltage ◽  
Occurrence Probability ◽  
Analysis Method ◽  
Factors Analysis ◽  
Industrial Big Data ◽  
Discrete Interval ◽  
Interval Value

Fault-influencing factors analysis is an important part of the quality supervision process. There are double functions for high-voltage switchgears that switch off and protect electric circuits in power transmission lines. Such devices have serious impact on power grid–operating efficiency, factory operation, and resident life, which will cause economic losses. As it was difficult for traditional methods to analyze fault-influencing factors accurately and comprehensively, a novel method based on industrial big data was proposed to analyze high-voltage switchgears fault-influencing factors in the process of quality supervision in this article, which integrated the qualitative and quantitative analyses method. In this model, the Classification Based on Multiple Class-Association Rules based on Gaussian Mixture Model as the qualitative analysis method was adapted to analyze the whole life cycle of fault-influencing factors of high-voltage switchgears comprehensively, and supplied fault-influencing factors with discrete interval value ranges. The logistic regression method based on qualitative analysis was constructed to calculate fault occurrence probability quantitatively, including the single-fault occurrence probability and the multiple-faults joint occurrence probability. In addition, the single-fault occurrence probability was used to modify the discrete interval value ranges calculated by the qualitative analysis method, which could make the ranges more accurately. Consequently, the proposed method could provide important reference for high-voltage switchgears operation maintenance, and it would be possible to design accurate maintenance plans before equipment failure. The final instance demonstrates the effectiveness of the proposed methodology.

Experimental Study of Elastic Modulus of Crumb Rubber Plastic Concrete

2010 ◽  
Vol 150-151 ◽  
pp. 1176-1183 ◽  
Author(s):  
Mei Zhou ◽  
Xiao Ming Yang ◽  
Kun Song
Keyword(s):  
Elastic Modulus ◽  
Influencing Factors ◽  
Crumb Rubber ◽  
Prediction Equation ◽  
Specimen Size ◽  
Analysis Method ◽  
Plastic Concrete ◽  
Binder Ratio ◽  
Crumb Rubber Concrete ◽  
Rubber Concrete

this paper got the compressive stress-strain fitting curve of crumb rubber plastic concrete, analyzed the influencing factors of elastic modulus of crumb rubber plastic concrete and found the influence law of specimen size and measuring distance to measured value of elastic modulus, through our experiments. The results of our experiments show that the method and operation of experiment strongly influence the measured value of elastic modulus of crumb rubber plastic concrete, but we can use the measures of step loading, screening and fitting curve to get the relatively exact measured value of elastic modulus of plastic concrete. And then, this paper analyzed a 16 sets of uniform experiment results with regression analysis method. As a result, we found the main influencing factors of elastic modulus of crumb rubber concrete are cement mixing amount, crumb rubber mixing amount and product of water-binder ratio and water reducer mixing amount, which the importance of them decreases progressively. Finally, this paper established the prediction equation of elastic modulus of crumb rubber concrete and found the connection of elastic modulus of crumb rubber concrete with specimen size and measuring distance.

Comparison and Analysis of Prediction Methods for Water Consumption per Ten Thousand Yuan Industrial Added Value

2014 ◽  
Vol 1073-1076 ◽  
pp. 2653-2658
Author(s):  
Zhi Jun Yan ◽  
Ming Yue Zhang ◽  
Chun Xiao Xu ◽  
Hai Tao Zhao ◽  
Yue Ping Tang ◽  
...  
Keyword(s):  
Water Management ◽  
Influencing Factors ◽  
Water Consumption ◽  
Management System ◽  
Added Value ◽  
Specific Situation ◽  
Water Efficiency ◽  
Analysis Method ◽  
Water Management System ◽  
Factors Analysis

Water consumption per ten thousand yuan industrial added value (WCPIAV) is the assessment indicator to implement the most stringent water management system to control water efficiency. This paper proposes trend analysis method, elasticity coefficient analysis method and influencing factors analysis method to predict WCPIAV in Jiangsu province, the experimental areas where implement the most stringent water management system. The results show that different methods predict well in different cities, influencing factors analysis method works better than the other two methods. An appropriate method should be selected depending on the specific situation.

scholarly journals Identifying Influencing Factors of Regional Agricultural Drought Vulnerability Based on PSR-TGRC Method

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Dongxing Zhang ◽  
Wenkai Cao ◽  
Bing Qi
Keyword(s):  
Influencing Factors ◽  
Agricultural Drought ◽  
Analysis Method ◽  
Drought Vulnerability ◽  
Relative Variation ◽  
Factors Affecting ◽  
Relational Analysis ◽  
Theoretical Support ◽  
Number Of Factors ◽  
Evaluation Problem

Regional agricultural drought vulnerability (RADV) is a complex nonlinear problem caused by the interaction of multiple factors, and an objective and systematic method is proposed by this paper to identify its influencing factors, which plays an important role in preventing and regulating the risks of regional agricultural drought. Firstly, to provide a reference for the evaluation problem in selecting the number of factors, the influencing factors affecting RADV are revealed by using the method of phase space reconstruction (PSR). Secondly, to rank the importance of influencing factors, a grey trend relational analysis (TGRA) method is proposed, considering the dynamic development relationship between the RADV index and the influencing factors and integrating the absolute and relative variation of sequences in each corresponding period. Finally, to reduce the collinearity between the influencing factors, a grey trend relational clustering (TGRC) analysis method is proposed. According to the above steps, the process of identifying factors based on PSR-TGRC method is formed. Taking Henan Province as an example, 14 main influencing factors and their effects on RADV are identified from all 42 factors, and the identification results which are consistent with the actual drought relief work show the rationality and practicality of PSR-TGRC method and provide theoretical support for formulating strategies of regional agricultural disaster prevention and mitigation.

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