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Article
Publication date: 1 August 2016

Qian Li

The purpose of this paper is to evaluate and rank the influence of internet public opinion of China’s Government work in 2015 by weighted absolute degree of grey incidence

Abstract

Purpose

The purpose of this paper is to evaluate and rank the influence of internet public opinion of China’s Government work in 2015 by weighted absolute degree of grey incidence with TOPSIS.

Design/methodology/approach

This disaggregation method includes four main steps, determine the vector of weights for the factors by analytic hierarchy process, calculate the matrix of consistent effect measure, determine the weighted absolute degree of grey incidence with TOPSIS, rank and evaluate the events.

Findings

We get the ranking of internet public opinion of China’s Government work in 2015 by weighted absolute degree of grey incidence with TOPSIS. The result can be used for evaluating and ranking the influence of internet public opinion in China. The positive weighted absolute degree of grey incidence, the negative weighted absolute degree of grey incidence and the weighted absolute degree of grey incidence with TOPSIS have the same ranking results. The same ranking results show that the method of weighted absolute degree of grey incidence with TOPSIS has good consistency.

Practical implications

The weighted absolute degree of grey incidence with TOPSIS can be easily used for other evaluation.

Originality/value

The weighted absolute degree of grey incidence with TOPSIS is proposed and first used for evaluating and ranking the influence of internet public opinion of China’s Government work.

Details

Grey Systems: Theory and Application, vol. 6 no. 2
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 3 August 2012

Ke Zhang, Wei Ye and Liping Zhao

This paper attempts to extend classic absolute degree of grey incidence so that the extended model can be used for grey number sequences.

Abstract

Purpose

This paper attempts to extend classic absolute degree of grey incidence so that the extended model can be used for grey number sequences.

Design/methodology/approach

The classic absolute degree of grey incidence was extended according to basic principles of grey incidence analysis. First, modelling methods and theories of the classic grey incidences were summarized. Then, the zeroing starting operator in grey incidence was extended for grey sequence. Third, the parameters in classic incidence degree were redefined, and an absolute degree of grey incidence for grey number sequences was proposed. The degree can not only be applied to grey number sequence, but also contains the uncertain information of analysis result. Fourth, two non‐linear programming models were constructed to estimate the grey coverage interval of absolute degree of incidences. Finally, the comparison method of grey numbers was introduced for sorting the different absolute degrees of incidences.

Findings

A theoretically feasible absolute degree of grey incidence was constructed for grey sequence. A case study showed that the proposed incidence degree was an effective method for grey sequence incidence analysis.

Practical implications

The method exposed in the paper can be used for grey sequences clustering, grey decision making, multi‐attribute decision making theory, uncertain target recognition and other related fields.

Originality/value

The paper succeeded in establishing an incidence analysis model for grey sequences which was still a research gap in grey system theory.

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Article
Publication date: 28 January 2011

Si‐feng Liu, Nai‐ming Xie and Jeffrey Forrest

The purpose of this paper is to solve the problems existing in traditional grey incidence models and advance several new grey incidence models based on visual angle of…

Abstract

Purpose

The purpose of this paper is to solve the problems existing in traditional grey incidence models and advance several new grey incidence models based on visual angle of similarity and nearness.

Design/methodology/approach

Based on the definition of traditional grey incidence models, two novel grey incidence models, grey similar incidence model and grey close incidence model, are studied in this paper. The interrelations and influence can be measured by the new models with different visual angle of similarity and/or nearness, respectively. The grey similar incidence model is used mainly to measure the similitude degree of the geometric patterns of sequence curves. The grey close incidence model is used mainly to measure the nearness of the sequence curves in space. The properties of the new models are discussed. It is proved that the proposed models are simplified methods to calculate the similitude degree and the close degree of grey incidence models.

Findings

The results show that the two novel grey incidence models satisfy the grey incidence axiom properly. It is useful to calculate the similitude degree and the close degree of two different sequences, and the process of calculating is easier than with traditional grey incidence models.

Practical implications

The method exposed in the paper can be used to calculate every two sequences. The similitude degree and the close degree of two different sequences can be given out. The method can also be used to rank sequences of more than two.

Originality/value

The paper succeeds in constructing two novel grey incidence models. The properties of novel model are studied and it is undoubtedly a new development in grey systems theory.

Details

Grey Systems: Theory and Application, vol. 1 no. 1
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 20 August 2018

Wenjie Dong, Sifeng Liu and Zhigeng Fang

The purpose of this paper is to study the modelling mechanisms of several grey incidence analysis models with great influence, including Deng’s grey incidence model…

Abstract

Purpose

The purpose of this paper is to study the modelling mechanisms of several grey incidence analysis models with great influence, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model; then analyse the problems to be solved in grey incidence analysis models; and clarify the applicable ranges of commonly used grey incidence models.

Design/methodology/approach

The paper comes to conclusions by means of comparable analysis. The authors compare several commonly used grey incidence analysis models, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model and give several examples to clarify the reasons why quantitative analysis results of different models are not exactly the same.

Findings

As the intension of each kind of incidence model is clear and the extension is relatively obscure, grey incidence orders calculated by different incidence models are often different. When making actual decisions, incompatible results may appear. According to different characteristics of extraction, grey incidence analysis models can be divided into three types: incidence model based on closeness perspective, incidence model based on similarity perspective and incidence model based on comprehensive perspective.

Practical implications

The conclusions obtained in this paper can help people avoid some defects in the process of actual selection and choose the better incidence analysis model.

Originality/value

The conclusions can be used as a reference and basis for the selection of grey incidence analysis models, it can help to overcome the defects and shortcomings of models caused by themselves and screen out more excellent analytical models.

Details

Grey Systems: Theory and Application, vol. 8 no. 4
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 3 April 2018

Jing Quan, Bo Zeng and LuYun Wang

Equally weighted factors and initial data from behavioural sequences are used for calculating the degree of grey incidence in Deng’s grey incidence analysis. However…

Abstract

Purpose

Equally weighted factors and initial data from behavioural sequences are used for calculating the degree of grey incidence in Deng’s grey incidence analysis. However, certain grey information cannot be directly obtained, and the correlation coefficients of each sequence at different times are of different importance to the system. The purpose of this paper is to propose an improved grey incidence model with new grey incidence coefficients and weighted degree of grey incidence. Some grey information can be obtained more easily by using the grey transformation sequences, and the maximum entropy method is used to calculate the weights of new grey incidence coefficients, so the new degree of grey incidence was distinguished more effectively by the proposed model.

Design/methodology/approach

New grey incidence coefficients are defined using transformation sequences of the initial data. To overcome the shortcomings arising from the use of equal weights, the maximum entropy method is proposed for determining the weights of the grey incidence coefficients. The resulting model optimises the classical models and evaluates the influencing factors more effectively. The effectiveness of the model was verified by a numerical example. Furthermore, the model was used for analysing the main influencing factors of the tertiary industry in China.

Findings

The proposed model optimises the classical models, and the application example shows that urbanisation has the greatest effect on employment in the tertiary sector.

Originality/value

An improved grey incidence model is proposed that improves the grey incidence coefficients and their weights, and has better performance than the classical models. The model was successfully used in the analysis of the influence factors of the tertiary industry in China. The results indicate that the model can reflect the significance of incidence coefficients at different time points; therefore, their fluctuation can be effectively controlled.

Details

Grey Systems: Theory and Application, vol. 8 no. 2
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 7 August 2017

Ke Zhang, Qiupin Zhong and Yuan Zuo

The purpose of this paper is to overcome the shortcomings of existing multivariate grey incidence models that cannot analyze the similarity of behavior matrixes.

Abstract

Purpose

The purpose of this paper is to overcome the shortcomings of existing multivariate grey incidence models that cannot analyze the similarity of behavior matrixes.

Design/methodology/approach

First, the feasibility of using gradient to measure the similarity of continuous functions is analyzed theoretically and intuitively. Then, a grey incidence degree is constructed for multivariable continuous functions. The model employs the gradient to measure the local similarity, as incidence coefficient function, of two functions, and combines local similarity into global similarity, as grey incidence degree by double integral. Third, the gradient incidence degree model for behavior matrix is proposed by discretizing the continuous models. Furthermore, the properties and satisfaction of grey incidence atom of the proposed model are research, respectively. Finally, a financial case is studied to examine the validity of the model.

Findings

The proposed model satisfies properties of invariance under mean value transformation, multiple transformation and linear transformation, which proves it is a model constructed from similarity perspective. Meanwhile, the case study shows that proposed model performs effectively.

Practical implications

The method proposed in the paper could be used in financial multivariable time series clustering, personalized recommendation in e-commerce, etc., when the behavior matrixes need to be analyzed from trend similarity perspective.

Originality/value

It will promote the accuracy of multivariate grey incidence model.

Details

Grey Systems: Theory and Application, vol. 7 no. 2
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 28 October 2014

Yong Wei and Kefang Zeng

– The purpose of this paper is to study the properties of comprehensive incidence degrees of closeness incidence degrees and similitude incidence degrees.

Abstract

Purpose

The purpose of this paper is to study the properties of comprehensive incidence degrees of closeness incidence degrees and similitude incidence degrees.

Design/methodology/approach

Based on the new definitions of the closeness incidence degree and the similitude incidence degree, the properties of comprehensive incidence of closeness incidence and similitude incidence are studied in this paper. It is proved that weighted arithmetic average of two closeness incidence degrees as well as power product (including weighted geometric average) of two closeness incidence degrees is still closeness incidence degree; and arithmetic weighted average of two similitude incidence degrees as well as power product (including weighted geometric average) of two similitude incidence degrees is still similitude incidence degree. Mixed weighted arithmetic average of closeness incidence degree and similitude incidence degree and mixed power product (including weighted geometric average) of closeness incidence degree and similitude incidence degree are closeness incidence degrees.

Findings

The result shows that the effect of closeness incidence degree is stronger than similitude incidence degree. As long as the weight of closeness incidence degree is not equal to zero, the comprehensive incidence degree results are closeness incidence degrees.

Practical implications

Grey incidence degrees have been widely applied in many fields, such as the test of grey model's forecasting effect, the system analysis and so on. The obtained result in this paper is to illustrate two kinds of incidence degrees are incompatible, namely there does not exist both closeness and similitude incidence degree.

Originality/value

The paper succeeds in showing that the attempt to get comprehensive incidence degree by arithmetic or geometric weighted average of closeness incidence degree and similitude incidence degree to reflect both closeness and similarity is in vain. And it is undoubtedly a new development in grey system theory.

Details

Grey Systems: Theory and Application, vol. 4 no. 3
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 27 January 2012

Bingjun Li, Chunhua He, Liping Hu and Yanhua Li

The purpose of this paper is to realize dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

Abstract

Purpose

The purpose of this paper is to realize dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

Design/methodology/approach

Starting from choosing influence factors on grain production and dividing the 30 years (from 1979 to 2009 year) of grain production in Henan province into three periods, the authors calculate grey incidence degree between grain yield and every influencing factor by grey incidence analysis method, respectively, then obtain the grey incidence order of influencing factors in every period. Also based on the three grey incidence orders from different periods, the authors find a changeable tendency of influencing factors on grain production and key influencing factors on grain production in different periods. Finally, to keep Henan province grain production stable and sustainable, several policy suggestions are given.

Findings

The results are convincing: it is effective and powerful to analyze dynamically influencing factors of grain production using grey systems theory, and it is urgent to strengthen agricultural science and technology input, and pay close attention to the influence of dosage of pesticide and fertilizers on grain production.

Practical implications

Grey incidence analysis and findings exposed in the paper can be used by agricultural firms to optimize grain production plans, and by government to formulate reasonable agricultural production policies.

Originality/value

The paper succeeds in getting dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.

Details

Grey Systems: Theory and Application, vol. 2 no. 1
Type: Research Article
ISSN: 2043-9377

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Article
Publication date: 7 August 2018

Dang Luo, Haitao Li and Qicun Qian

The purpose of this paper is to construct a key factors selection approach for a class of small-sample multi-factor cross-sectional data analysis (SMCDA) problem, which is…

Abstract

Purpose

The purpose of this paper is to construct a key factors selection approach for a class of small-sample multi-factor cross-sectional data analysis (SMCDA) problem, which is very common in productive practice and scientific research, such as coal-bed methane (CBM) content analysis, civil aircraft cost analysis, etc. Key factors selection is an important basic work for SMCDA problem; the proposed method is constructed to improve the accuracy and explanatory of the selected key factors.

Design/methodology/approach

Using grey system theory to solve SMCDA problem is more reasonable under few data and poor information. Therefore, this paper constructs a grey incidence analysis (GIA) model with rate of change to select the key factors of an SMCDA problem. The basic idea of the proposed method is to simulate time series by randomly sorting the selected samples, and to calculate the degree of grey incidence with rate of change by loop iterative algorithm, then to construct the degree matrix of grey incidence with rate of change, and finally by which, to utilise quantitative and qualitative analysis methods to select the key factors.

Findings

The experimental analysis of application cases demonstrates that the key factors of system’s characteristic can be successfully screened out by the proposed method, the results are consistent with actual conditions, and they have a clearer meaning and a better interpretability.

Practical implications

The method proposed in this paper could be utilised to select key factors for such a class of SMCDA problem, which has fewer observation samples (small-sample), which is influenced by a number of factors (multi-factor) and whose observation samples are placed randomly rather than by time (cross-sectional data). Taking the key influence factors of CBM content and the key driving factors of the vulnerability of agricultural drought in Henan as examples, the results proved the feasibility and superiority of this proposed method.

Originality/value

Most of the existing GIA models mainly focus on these classes of issues with time series data or panel data. However, few GIA models take SMCDA problem as the research object. In this paper, the authors develop the GIA model with rate of change according to the characteristics of SMCDA problem, and present some properties and application suggestions of the proposed method.

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Article
Publication date: 1 February 2016

Sifeng Liu, Yingjie Yang, Naiming Xie and Jeffrey Forrest

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new…

Abstract

Purpose

The purpose of this paper is to summarize the progress in grey system research during 2000-2015, so as to present some important new concepts, models, methods and a new framework of grey system theory.

Design/methodology/approach

The new thinking, new models and new methods of grey system theory and their applications are presented in this paper. It includes algorithm rules of grey numbers based on the “kernel” and the degree of greyness of grey numbers, the concept of general grey numbers, the synthesis axiom of degree of greyness of grey numbers and their operations; the general form of buffer operators of grey sequence operators; the four basic models of grey model GM(1,1), such as even GM, original difference GM, even difference GM, discrete GM and the suitable sequence type of each basic model, and suitable range of most used grey forecasting models; the similarity degree of grey incidences, the closeness degree of grey incidences and the three-dimensional absolute degree of grey incidence of grey incidence analysis models; the grey cluster model based on center-point and end-point mixed triangular whitenization functions; the multi-attribute intelligent grey target decision model, the two stages decision model with grey synthetic measure of grey decision models; grey game models, grey input-output models of grey combined models; and the problems of robust stability for grey stochastic time-delay systems of neutral type, distributed-delay type and neutral distributed-delay type of grey control, etc. And the new framework of grey system theory is given as well.

Findings

The problems which remain for further studying are discussed at the end of each section. The reader could know the general picture of research and developing trend of grey system theory from this paper.

Practical implications

A lot of successful practical applications of the new models to solve various problems have been found in many different areas of natural science, social science and engineering, including spaceflight, civil aviation, information, metallurgy, machinery, petroleum, chemical industry, electrical power, electronics, light industries, energy resources, transportation, medicine, health, agriculture, forestry, geography, hydrology, seismology, meteorology, environment protection, architecture, behavioral science, management science, law, education, military science, etc. These practical applications have brought forward definite and noticeable social and economic benefits. It demonstrates a wide range of applicability of grey system theory, especially in the situation where the available information is incomplete and the collected data are inaccurate.

Originality/value

The reader is given a general picture of grey systems theory as a new model system and a new framework for studying problems where partial information is known; especially for uncertain systems with few data points and poor information. The problems remaining for further studying are identified at the end of each section.

Details

Grey Systems: Theory and Application, vol. 6 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

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