Grey Relational Model Research Articles

A Method for Traffic Congestion Clustering Judgment Based on Grey Relational Analysis

Traffic congestion clustering judgment is a fundamental problem in the study of traffic jam warning. However, it is not satisfactory to judge traffic congestion degrees using only vehicle speed. In this paper, we collect traffic flow information with three properties (traffic flow velocity, traffic flow density and traffic volume) of urban trunk roads, which is used to judge the traffic congestion degree. We first define a grey relational clustering model by leveraging grey relational analysis and rough set theory to mine relationships of multidimensional-attribute information. Then, we propose a grey relational membership degree rank clustering algorithm (GMRC) to discriminant clustering priority and further analyze the urban traffic congestion degree. Our experimental results show that the average accuracy of the GMRC algorithm is 24.9% greater than that of the K-means algorithm and 30.8% greater than that of the Fuzzy C-Means (FCM) algorithm. Furthermore, we find that our method can be more conducive to dynamic traffic warnings.

Capacity Evaluation Model of Enterprise Technological Innovation Complex System and Its Application

Under the background of complex system of enterprise innovation, based on the selforganization theory and collaborative theory, it is thought that the enterprise technology innovation system belongs to the grey system, for this reason, build the grey relational analysis model of the enterprise technology innovation system capability evaluation, and use weight coefficient method to optimize. Finally, use the optimization model to evaluate the technological innovative ability of seven enterprises; the results show that the built enterprise technology innovation system ability evaluation model is effective, and it can offer the innovation ability value of different enterprises accurately, providing the useful decision-making reference for the enterprise technology innovation system and the optimization of technological innovation cooperative system.

Effects of Land Use Change on Phosphorus Levels in Surface Waters—a Case Study of a Watershed Strongly Influenced by Agriculture

Phosphorus (P) loss from diffuse sources remains as the main cause of freshwater eutrophication in agricultural regions. The amount of land used for different agricultural practices may be a strong explanatory factor for the P loading to runoff waters. A prerequisite is that the effect of changes in land use on P levels in surface waters needs to be ascertained and quantified. In this study, a comprehensive approach has been developed to explore the environmental consequences of P levels in receiving water with corresponding land use change in a heavily agriculturally influenced watershed. A coupled simulation using Dyna-CLUE model with grey relational analysis (GRA) and grey model GM (1,1) model was employed to stimulate spatial distribution and area demand. Besides, a comprehensive land use index with degree of P saturation (DPS%) as weight coefficient was developed to examine the statistical and spatial relationships of land use and P levels in receiving waters on regional watershed. Moreover, in order to evaluate the practical impact of land use change on water quality, a planned emigration and watershed ecological reconstruction planning were designed into the scenarios. The potential of changes in land use as an abatement action to curb eutrophication was evaluated by modelling the effect of issued emigration and ecological restoration programs in the local watershed of the Yuqiao water reservoir in northeastern China. Kappa indexes above 0.85 for the validation period verify that the coupled land use change model is able to simulate the effect of the abatement actions on land use. Scenario predictions reveals that local emigration and a comprehensive ecological restoration project as abatement actions could significantly decrease contents of P in receiving surface waters: Relative to year 2012, total P and orthophosphate could be reduced by 36 and 45 %, respectively, by the end of year 2018. This modelling approach can, with moderate modifications, also be adapted to other watersheds. The model developed in this study can thus be used by environmental managers as a tool to identify risk for P loss from diffuse sources within a watershed and assist policy makers to assess the effect on P losses by implementing abatement actions that changes land use.

The study on key influencing factors of mergers and acquisitions performance based on China state-owned listed enterprises

Purpose – The purpose of this paper is to analyze the key influencing factors which affect the performance of M & A and the key influencing factors by establishing grey relational sequence model. The results can not only perfect the current existing theoretical system, but also provide theoretical guide for M & A practice. Design/methodology/approach – First of all, this paper analyzes the M & A performance through the literature reviews, and then establishes the grey model about M & A performance from three influencing factors: profitability, operational and development capacity to analyze its key influencing factors which affect M & A performance. Furthermore, the key factors influencing of M & A performance are analyzed, the results can be obtained through the analysis of the grey relative degree based on six years’ data of state-owned enterprises. Findings – In this paper, some results can be found that ownership restriction and executive compensation can significantly affect corporate profitability and operation ability. M & A and institutional investors can be affected greater from the perspective of development ability and profitability. In general, enterprise scale has little affect on the performance after M & A. Practical implications – With the sustainable development of economic globalization, M & A has become an important strategy for the rapid growth of the enterprise, enlargement market and brand effect. But the performance after M & A in most enterprises does not improve. As the pillar of the national economy, state-owned enterprises have an important impact on China’s economic development and urgently need to be reformed. Originality/value – This paper analyzes the key factors through establishing grey relative sequence model to analyze the correlation of M & A performance and influencing factors, and finds key influencing factors which affect the performance of M & A. The conclusion can provide policy guidance for the improvement of M & A performance in the future.

Sports Industry and Economic Development Correlation Degree Research Based on Grey Relational Degree Model

Sports Industry and Economic Development Correlation Degree Research Based on Grey Relational Degree Model

Design of Intelligent Wearable Device Based on Grey Relational Analysis Model

Design of Intelligent Wearable Device Based on Grey Relational Analysis Model

Relational Research between China’s Marine S&T and Economy Based on RPGRA Model

To make up the defect of the existing model, an improved grey relational model based on radian perspective (RPGRA) is put forward. According to the similarity of the relative change trend of time series translating traditional grey relational degree into radian algorithm within different piecewise functions, it greatly improves the accuracy and validity of the research results by making full use of the poor information in time series. Meanwhile, the properties of the RPGRA were discussed. The relationship between China’s marine S&T and marine economy is researched using the new model, so the validity and creditability of RPGRA are illustrated. The empirical results show that marine scientific and technological research projects, marine scientific and technological patents granted, and research funds receipts of the marine scientific research institutions have greater relationship with GOP, which indicates that they have more impact on China’s marine economy.

A Grey Relational Analysis Model of Scientific Research Ability on Music Based on AHP and Its Realization

A Grey Relational Analysis Model of Scientific Research Ability on Music Based on AHP and Its Realization

Estimating civil aircraft’s research and manufacture cost by using grey system model and neural network algorithm

Purpose – The purpose of this paper is to propose novel civil aircraft cost parameters’ selection method and novel cost estimation approach for civil aircraft so as to effectively simulate or forecast civil aircraft cost under poor information and small sample. Design/methodology/approach – Based on existent cost estimation indexes, this paper summarized civil aircraft research and manufacturing cost impact index system and adopted grey relational model to select most important impact factors. Consider civil aircrafts’ cost information could not be easily collected, the author must estimate their costs with limited sample and poor information. A combination model of GM (0, N) model and BP neural network algorithm is proposed. Both advantages of simulation of BP neural network algorithm and poor information generation of GM (0, N) were effectively combined. Then steps of combined model were given out. Finally, nine types of aircrafts were used to test the validity of proposed model. As comparing with the traditional multiple linear regression model and simple GM (0, N) model, results indicated that proposed model can do the work better. Findings – Grey relational model can be applied for parameters’ selection and combined GM (0, N) model and BP neural network algorithm can estimate aircraft’s cost as well. Results show that novel combined model could get high forecasting accuracy. Practical implications – Cost estimation is key problem in production management of civil aircraft. Effective cost management could promote competitiveness of aircraft manufacturing company. Proposed combined model can be applied for civil aircraft cost estimation. Similarly, it could be applied for other complex equipment cost estimation. Originality/value – The paper succeeds in proposing grey relational model for cost parameters’ selection and constructing a combination model of GM (0, N) model and BP neural network algorithm. Algorithm of the proposed model was discussed and steps were given out.

A Comparison between Statistical Analysis and Grey Model Analysis on Assessed Parameters of Petroleum Potential from Organic Materials

This study aims to investigate the impact of changes in the Tmax and Ro% on the assessed parameters (S1, S2, S1+S2, HI, QI, BI, PI, TOC) of petroleum potential of organic materials. The samples studied include coals and coaly shales of Mushan Formation, Shihti Formation and Nanchuang Formation in NW Taiwan, coals and an oil shale from Mainland China, the well-drilled chip samples from NW Australia, in addition to the data of samples were included from literatures. This work will get on the detecting data of 10 parameters (S1, S2, S1+S2, TOC, HI, QI, BI, PI, Ro%, Tmax) and progressing statistical analysis, and focus the study on comparison between grey forecast of grey relational grade and regression model forecast. The results from statistical analysis (include temperature-treated samples were individually subjected to Rock-Eval analysis) of the all parameters data for all samples in this research project, not only be executed a linear regression, curve regression between any two parameters, and multivariate regression, but also be carried on the forecast of grey correlation grade of grey theory (include grey relational generating (Nominal-the-better-:Ro%; Larger-the-better-: Tmax, HI, QI, BI, S2, S1+ S2, S1; smaller-the-better-: TOC, PI) and globalization grey relational grade). So far, obtain roughly the consistency of results from two type predictive analysis. The constructed HI, QI and BI bands were broad at low maturities and gradually narrowed with increasing thermal maturity. The petroleum generation potential is completely exhausted at a vitrinite reflectance of 2.0-2.2% or a Tmax of 510-520°C. An increase in HI and QI suggests extra petroleum potential related to changes in the structure of the organic material. A decline in BI signifies the start of the oil expulsion window and occurs within the vitrinite reflectance range 0.75-1.05 % or a Tmax of 440-455 oC. Furthermore, petroleum potential can be divided into four different parts based on the cross-plot of HI vs. %Ro. The area with the highest petroleum potential is located in sectionⅡ with %Ro=0.6-1.0%, and HI>100. Oil generation potential is rapidly exhausted at section Ⅲ with %Ro >1.0%. This result is in accordance with the regression curve of HI and QI with %Ro based on 97 samples with %Ro=1.0~5.6%.

Corrosion Inhibition: Synergistic Influence of Gluconates on Mild Steel in Different Corrosive Environments. Synergetic Interactions of Corrosion Inhibition Tendency of Two Different Gluconates on Mild Steel in Different Corrosive Environments

S usceptibility of mild steel to corrosion attack has restricted its industrial appl ications , despite its numerous advantageous characteristics. Comparison of the inhibitive tendency of a mixture of zinc gluconate (ZG) and ferrous gluconate (FG) on the corrosion behavior of mild steel in acid and saline media was investigated using electr ochemical and weight loss techniques. The FG:ZG ratio was dosed from 0.5:0.5 to 2.0:2.0 g/v at an interval of 0.5:0.5. The surface morphology of the corroded mild steel samples was evaluated by high resolution scanning electron microscope equipped with ene rgy dispersive spectroscopy (HR - SEM/EDS). Experimental results indicated that the combined inhibitor significantly reduced the corrosion rates of mild steel, with the maximum inhibition efficiency (IE) of 100% and 48% at 28 o C in the presence of 1.5:1.5 g/ v concentrations in 3.5 % NaCl and 0.5 M H2SO4 solutions , respectively. The SEM micrographs of the inhibited samples show a clearly reduced surface degradation as opposed to the surface morphology without inhibitor. Potentiodynamic polarization curves stud ies showed that the combined inhibitor is a mixed type inhibitor for mild steel corrosion in 3.5 % sodium chloride and 0.5 molar sulphuric acid solutions. From the set of experimental data it was found that the combined inhibitor reduced the corrosion rate through an adsorption process and obeyed Langmuir’s adsorption isotherm in chloride medium and Freundlich adsorption isotherm in sulphuric acid medium at all concentrations and temperature studied. Good synergism exists between FG and ZG. The results obta ined from potentiodynamic polarization are consistent with the results of the weight loss method. Synergistic performance of inhibitors was perfect in saline medium. From the analysis of grey relational grade model, the significant concentration ratios wer e indentified. The results showed the influence of synergistic FG:ZG at a concentration of 1.5 g/v on the corrosion rate of mild steel. P redicted results were found to be in good agreement with experimental results .

Prediction of the vertical vibration of ship hull based on grey relational analysis and SVM method

There are certain limitations when empirical formulas are used to predict the ship hull vertical vibration. Natural frequency of ship’s vertical vibration is predicted by support vector machine (SVM), which possesses many characteristics such as small sample learning, global optimization and strong generalization. Considering the parameters that influence the natural frequency of ship’s vertical vibration are much more, a grey relation model between ship’s main parameters and natural frequency of ship’s vertical vibration is established by grey relational analysis theory to get the grey correlation degree of each parameter. The parameters with greater correlation degree are used as input data and the measured values of natural frequency of vertical vibration are used as output data in SVM to build the nonlinear regression model of the natural frequency of vertical vibration. Natural frequencies of eight ships’ vertical vibration are predicted by the nonlinear regression model, and the results are coincident with the measured values. The proposed method in this paper is proved to be accurate and feasible, which provides a new idea to the prediction of natural frequency of ship’s overall vertical vibration.

Research of Factors of Regional Product Quality Based on Gray Relational Analysis

This paper took the regional product quality asthe object of study. Firstly this paper took advantageof PESTEL model tostudy factors of regional product quality from the enterprise external environmentand strategic perspective. Built regional product quality indicator system ofsix aspects from political, economic, social,technological, environment and legal. Then established evaluation modelby gray relational analysis model. The next step is to analyze the variousfactors by expert scoring method. The results can show the influence degree offactors. Scienceand technology spending, Regional GDP are Local fiscal revenue are the topthree important factors. Finally, based on the evaluationresults of the analysis, provided a reference for improving the quality ofregional products.

The Application of Grey Relational Analysis Model in the Performance Evaluation of Agricultural Product Logistics Companies

In this paper, the use of gray relational analysis theory and methods, Evaluation for agricultural logistics and enterprise performance evaluated. The results obtained using the comprehensive evaluation can provide an objective for the logistics enterprise managers, rational basis for decision making. Innovation of this paper is to use gray relational model to widen, the calculation methods of gray correlation degree of improvement.

Research on tourism development of Xinjiang based on grey relational analysis and gravity model

Purpose This paper attempts to apply grey correlation analysis method and gravity model to solve the research on Xinjiang tourism resources strategic development , which can be viewed as an important part of the problems of Xinjiang tourism economic development. Design/methodology/approach Starting from the fact that the unbalanced development of local tourism economy often appears in Xinjiang tourism economic development.On the basis of the theory of grey relational analysis of Ju-long Deng and the theory of gravity model of Smith D and Haggett P, this paper systematically utilizes the grey relational analysis to analyze the key factors affecting tourism economy in Xinjiang ,and apply gravitational model to analysis tourism impact degree Between different areas in Xinjiang. Findings The results show that different areas of Xinjiang are in the oasis belt, the economic level is not balanced, effects of passenger volume and civilian vehicle number of tourism economy is relatively large. In addition, the stu...

Data Processing in the Application of Grey Relational Analysis Model in Regional Economic Openness of Evaluation System

In the process of multi index analysis and evaluation, the index value is normalized and standardized through non-dimensional processing of the original data. The index weight is determined according to each index relative principal component contribution through principal component analysis and principal component extraction. Then, a combined evaluation model will be formed through the grey relational analysis, calculation of each index according to grey weighted relative degree. Scientific applicability of the model will be evaluated through regional economic opening degrees.

Comprehensive Evaluation to Distribution Network Planning Schemes Using Principal Component Analysis Method

Aiming to the complexity of vibration fault cause, the great many of fault parameters in hydroelectric generating set, and the superiority of grey relation analysis for its no strict requirement to fault sample capacity and regularity, the weighted grey relation model is built to look for the vibration fault type. The fuzzy matrix's transformation arithmetic is used to obtain the weight vectors of the grey relation coefficient, thus the weighted coefficient is the weighted grey relation model. The relation coefficient between reference sequence and compare sequence in vibration fault sample is provided by synthetic arithmetic of fuzzy weight to diagnose the vibration fault type. The grey relation coefficient weighted by fuzzy synthetic arithmetic, which is not only made the established weight be a scientific basis, but also can “sensitive” highlight the vibration fault type of hydroelectric generating set. Thus the problem of looking for every fault types is better resolved. By analyzing the practical example, it proved that the weighted grey relation model in the paper can effectively diagnose the vibration fault type of hydroelectric generating set and it has definite applicability.

A Complex Network Analysis of the Top College Coaches

To find the best all time college coach, we analyze synthetically the college coaches of all time in the field of football. First, we collect the necessary data and build the index set which is composed of Win-Loss percentage, SRS, SOS, Championship index and Games. After screening the data with the vital indexes like Win-Loss percentage and Games, we select the coaches who are qualified to be the best one. In view of the effect of the time line horizon, we rank the coaches annually with grey relational analysis model based on Entropy Method. Since there are only a portion of coaches to be ranked in one year, we set up top coach network to link all coaches, in which vertexes refer to coaches. Applying the network, we calculate the prestige score and correct it by considering the effect of the strength of teams. With the help of prestige score, we gain the final rank.

Fuzzy grey relational analysis of design factors influencing on maintainability indices

Maintainability is a design attribute of a product, and its relationship with the design factors is complicated. In consideration of the fuzziness and uncertainty of design factors that influences the product's maintainability indices, we propose a method based on fuzzy grey relational analysis to determine their prioritization in this paper. First, the evaluation methods of various design factors and how these factors affect product maintainability indices are analyzed. Then, the fuzzy grey relational analysis model of the relationship between the design factors and maintainability indices is set up, and the prioritization of design factors to maintainability indices is achieved. Finally, the proposed methods are applied on a subsystem of a manned spacecraft, which indicates that the proposed method can quantitatively analyze the influencing degree of the design factors to maintainability indices. This information can be used to guide maintainability indices evaluation modeling based on digital mock-up in the design phase and help to catch the major influencing design factors in maintainability design.

Developing e-store marketing strategies to satisfy customers' needs using a new hybrid gray relational model

With the increasing popularity of online shopping services, e-stores are experiencing ever more fierce competition. Thus, it is imperative that managers take steps to improve their services and ensure customer loyalty, and this can only be done by understanding their customers' needs and developing appropriate marketing strategies. Therefore, the aim of this paper is to propose a new hybrid gray relational model to enhance strategies by adopting innovation and creativity to achieve the aspiration level in each dimension/criterion of satisfying/promoting human life and convenient service. This new hybrid gray relational model, which can improve the performance of each criteria to close the aspiration level of each reference point, will address interdependent problems among dimensions/criteria in the real world and provide feedback. More specifically, a DANP (DEMATEL-based ANP) and a gray relational assessment model will be combined to produce an influential network relationship map (INRM), showing the influential weights and gaps between the actual performance and the level of aspiration. As such, the contribution made by this research will be to produce the best strategies for e-store managers to improve their business model in order to meet customers' needs, encourage them to repurchase, and to enable stores to provide the most effective and efficient service for their customers.