Discrimination for Bidders’ Parallel String Based on the AHP–Fuzzy

2014 ◽  
Vol 584-586 ◽  
pp. 2700-2704
Author(s):  
Qi Guo ◽  
Kai Li ◽  
Zhi Ding Chen
Keyword(s):  
Correlation Analysis ◽  
Comprehensive Evaluation ◽  
Influence Factors ◽  
Fuzzy Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Grey Correlation ◽  
Annual Output ◽  
Grey Correlation Analysis

Collusion behaviors in the market are divided into three types: rotation, price alliance and compensation bid. Constructing AHP-Fuzzy model evaluates bidders’ parallel string behaviors. It is judged with the aid of grey correlation analysis and fuzzy comprehensive evaluation. Price correlation, price rationality and the annual output value rate of the total assets are taken as influence factors of comprehensive evaluation. Finally, an example proves the correctness and effectiveness of the model.

Land Value Evaluation of Real Estate Development Project Based on Grey Correlation Analysis

2013 ◽  
Vol 438-439 ◽  
pp. 1782-1785
Author(s):  
Wei Ran Wang ◽  
Yun Xiu Sai ◽  
Xing Fang
Keyword(s):  
Real Estate ◽  
Correlation Analysis ◽  
Influence Factors ◽  
Development Project ◽  
Real Estate Development ◽  
Land Value ◽  
Analysis Model ◽  
The Real Estate ◽  
Grey Correlation ◽  
Grey Correlation Analysis

The accuracy of land value directly affects the size of the project development profit in real estate development project, more will be related to the project success and failure. According to the characteristics of the real estate development, land prices in the mature real estate, on the basis of influence factors, the grey correlation analysis model is set up by using the value of developed successful plot, to estimate the land value, and combined with examples to provide a reference for scientific decision-making to real estate developers.

scholarly journals Grey Correlation Analysis on Travel Modes and their Influence Factors

2017 ◽  
Vol 174 ◽  
pp. 347-352 ◽  
Author(s):  
Shanshan Fang ◽  
Xinsheng Yao ◽  
Junqi Zhang ◽  
Meng Han
Keyword(s):  
Correlation Analysis ◽  
Influence Factors ◽  
Grey Correlation ◽  
Grey Correlation Analysis

Grey Correlation Analysis of Sensitive Factors of Concrete Structures Durability

2008 ◽  
Vol 400-402 ◽  
pp. 471-476
Author(s):  
Jian Xin Liu ◽  
Ben Liang Liang
Keyword(s):  
Correlation Analysis ◽  
Influence Factors ◽  
Concrete Structures ◽  
Traditional Methods ◽  
Grey Correlation ◽  
Number Of Factors ◽  
Durability Design ◽  
Grey Correlation Analysis ◽  
Correlation Analysis Method ◽  
Grey Correlation Theory

Concrete structures durability is affected by a number of factors which have different sensitivity. According to level of sensitivity classified the influence factors could promote concrete structures durability design. The disadvantage of traditional methods of sensitivity analysis in concrete structures durability is the larger number of samples. The grey correlation theory was used to analyze the degree of the sensitivity of the influence factors and comparison with traditional methods of calculation. The results show that the grey correlation analysis method could quantify the levels of the sensitive factors and with higher reliability. A new way to study the durability of concrete structures was provided.

A Multi-Factor Comprehensive Evaluation Method for Pipeline Integrity

2019 ◽  
Author(s):  
Jing Yang ◽  
Xiaolin Wang
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Correlation Analysis ◽  
Evaluation Method ◽  
Residual Life ◽  
Comprehensive Evaluation ◽  
Comprehensive Evaluation Method ◽  
Grey Correlation ◽  
Grey Correlation Analysis ◽  
Artificial Neural

Abstract Pipeline integrity management is widely used as an effective means for pipeline safety management, in which integrity evaluation is an important part. To some extent, pipeline integrity can be interpreted as the safety condition of the pipeline, while safety is an eternal topic for pipeline operators. In numerous recent studies, the evaluation of pipeline integrity generally focuses on the evaluation of remaining strength and/or residual life, which is based on the defect size such as corrosion, dents, etc., obtained during inspection. However, pipeline integrity is not only related to the pipe body, all factors that may threaten the operation safety of the pipe should be considered, including the pipe body, ancillary facilities, the pipe security system, and the surrounding environment, etc.. Although some comprehensive models have been established recently to assess pipeline condition, there still exist limitations for practical application, such as quantification of integrity and complexity of analysis. Therefore this paper presents the development of a comprehensive integrity evaluation method based on multi-factor analysis. The method is developed by an integrated application of fuzzy mathematics, grey correlation analysis theory, and the artificial neural network technique. After establishing integrity evaluating indexes, fuzzy analysis is used to quantify and classify pipeline integrity, and grey correlation analysis to screen key influence indicators. Then a comprehensive predictive evaluation model can be generated using large amount of relevant sample data based on the artificial neural network technique. In the end of the paper, a simple case is applied to validate feasibility of this comprehensive integrity evaluation method. The comprehensive evaluation method is expected to be applied to determine the condition of pipeline integrity, and to grade and rank the integrity condition of pipes, so as to assist and optimize pipeline maintenance decision for pipeline operators.

The empirical study of executive compensation in China port and shipping listed companies based on the grey relational analysis

2016 ◽  
Vol 6 (2) ◽  
pp. 259-269 ◽  
Author(s):  
Jiajia Chen ◽  
Rong Zhang ◽  
Bin Liu
Keyword(s):  
Firm Performance ◽  
Correlation Analysis ◽  
Executive Compensation ◽  
Influence Factors ◽  
Listed Companies ◽  
Grey System Theory ◽  
Financial Indicators ◽  
Content Type ◽  
Grey Correlation ◽  
Grey Correlation Analysis

Purpose – The purpose of this paper is to find the key influence factors of executive compensation within China ports and listed shipping companies and provide some reasonable suggestions. Eventually, help to perfect the executive compensation evaluation mechanism against the background of new area. Design/methodology/approach – Grey correlation analysis is an important part of grey system theory. Professor Liu Sifeng further studies the relationship between two sequences absolute increment on the basis of Deng’s degree and put forward the “Grey absolute correlation degree,” which is widely used in practice. In the study, on the basis of the area of the line between sequences size, it measures the correlation degrees of firm performance, executive stock holding, continuous growth capacity and other relevant factors of executive payment in China ports and listed shipping companies. Findings – The paper concludes that the main factors influence CEO salary in China ports and listed shipping companies are return on equity and growth rate of fixed assets. However, the authors consider the frequent occurrence of executives’ corruption in China listed state-owned enterprise under the environment of financial and economic crisis, the authors argue that the significant influence of net assets attributed to shareholders cannot be ignored. In addition, cash flow in operating activities and executive stock holding both have relatively important effect on executive compensation. Research limitations/implications – This paper still has some limitations. First, it merely takes into account the financial indicators and ignores the influence of non-financial indicators to the performance evaluation of listed companies, such as: innovation ability, human capital and goodwill. Second, it has not considered the power consumption and other types of “invisible income” in the executive compensation structure, neither the influence of investing and financing activities on corporate performance. Consequently, these are likely to cause a certain deviation to the results of the study. Practical implications – The outcome obtained in this paper can be provided for China ports and listed shipping companies to establish a reasonable executive compensation evaluation and incentive mechanism under the background of depressed shipping market. Social implications – This paper intends to use correlation analysis between firm performance, executive stock holding, sustainability and executive compensation in the new area of time, tries to make a greater contribution to the major component of salary policy and then make some suggestions on incentive supervising and restraining mechanisms for the ports and listed shipping firms in China. Originality/value – Although scholars have done many studies about the association analysis of executive compensation and firm performance, they neglect the economic environment of industry. Meanwhile, considering the non-financial indicators and incomplete information, this paper studies the grey correlation analysis of executive compensation and influence factors in China ports and listed shipping firms under the background of the Chinese flagging shipping industry.

Grey Correlation Analysis Method and its Application in the Field of Engineering

2014 ◽  
Vol 631-632 ◽  
pp. 250-253
Author(s):  
Ying Wei
Keyword(s):  
Correlation Analysis ◽  
Influence Factor ◽  
Influence Factors ◽  
Housing Price ◽  
Grey System Theory ◽  
Housing Construction ◽  
Analysis Method ◽  
Grey Correlation ◽  
Grey Correlation Analysis ◽  
Commercial Housing

Grey system theory has been applied widely in the fields of industry and engineering such as property industry. In this paper, we study the influence factors on the housing price of property industry, and present an influence factor analysis method based on the grey correlation analysis. Then this method is used to analyze the multiple influence factors on property industry such as GDP, population, the total amount of real estate investment, commercial housing construction area, completed commercial housing area, commercial housing sales area and urban per capita disposable income, then we conclude that the commercial housing sales area and commercial housing construction area are two main influence factors on housing price.

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