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Article
Publication date: 2 November 2015

Si-feng Liu, Yingjie Yang, Zhi-geng Fang and Naiming Xie

The purpose of this paper is to present two novel grey cluster evaluation models to solve the difficulty in extending the bounds of each clustering index of grey cluster

Abstract

Purpose

The purpose of this paper is to present two novel grey cluster evaluation models to solve the difficulty in extending the bounds of each clustering index of grey cluster evaluation models.

Design/methodology/approach

In this paper, the triangular whitenization weight function corresponding to class 1 is changed to a whitenization weight function of its lower measures, and the triangular whitenization weight function corresponding to class s is changed to a whitenization weight function of its upper measures. The difficulty in extending the bound of each clustering indicator is solved with this improvement.

Findings

The findings of this paper are the novel grey cluster evaluation models based on mixed centre-point triangular whitenization weight functions and the novel grey cluster evaluation models based on mixed end-point triangular whitenization weight functions.

Practical implications

A practical evaluation and decision problem for some projects in a university has been studied using the new triangular whitenization weight function.

Originality/value

Particularly, compared with grey variable weight clustering model and grey fixed weight clustering model, the grey cluster evaluation model using whitenization weight function is more suitable to be used to solve the problem of poor information clustering evaluation. The grey cluster evaluation model using endpoint triangular whitenization weight functions is suitable for the situation that all grey boundary is clear, but the most likely points belonging to each grey class are unknown; the grey cluster evaluation model using centre-point triangular whitenization weight functions is suitable for those problems where it is easier to judge the most likely points belonging to each grey class, but the grey boundary is not clear.

Details

Grey Systems: Theory and Application, vol. 5 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 8 January 2018

Peng Li and Cuiping Wei

In multi-criteria decision-making with interval grey number information, decision makers usually take a risk to rank or choose some very similar alternatives…

Abstract

Purpose

In multi-criteria decision-making with interval grey number information, decision makers usually take a risk to rank or choose some very similar alternatives. Additionally, when evaluating only one alternative, decision makers can only obtain a specific value using traditional decision-making methods and may find it hard to cluster the alternatives to the “correct class” because these methods lack predetermined reference points. To overcome this problem, this paper aims to propose a two-stage grey decision-making method.

Design/methodology/approach

First, a new type of clustering method for interval grey numbers is designed by proposing a new possibility function for grey numbers. Based on this clustering method, a new grey clustering evaluation model for interval grey numbers is proposed by which decision makers can obtain the grade rating information of each alternative. Then, according to the grey clustering evaluation model, a new two-stage decision-making method is introduced to solve the problem that some alternatives are very similar by designing a grey comprehensive decision coefficient of alternatives.

Findings

The authors propose a new grey clustering evaluation model to deal with interval grey numbers. They design a new model to obtain the membership degree for the interval grey numbers and then propose a new grey clustering evaluation model, which can evaluate only one alternative by predefined grey classes. Then, by the grey comprehensive decision coefficient, a two-stage grey evaluation decision-making method is put forward to solve the problem that some alternatives are very close and hard to be distinguished.

Originality/value

A new grey clustering evaluation model is proposed, which can evaluate only one alternative by predefined grey classes. A two-stage grey evaluation decision-making method is given to solve the problem that some alternatives are very close and hard to be distinguished.

Details

Kybernetes, vol. 47 no. 4
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 7 November 2016

Jianghui Xin

With the improvement of economic level, car ownership is growing, and the number of scrapped automobiles is increasing. Therefore, evaluation research for auto parts…

3600

Abstract

Purpose

With the improvement of economic level, car ownership is growing, and the number of scrapped automobiles is increasing. Therefore, evaluation research for auto parts remanufacturing is particularly important. The purpose of this paper is to construct the evaluation index system of auto parts remanufacturing and research the grey clustering theory. The grey fixed weight clustering evaluation is used to evaluate automobile engine remanufacturability.

Design/methodology/approach

According to the policies and regulations of China about remanufacturing, economic, technical, resources, energy and the environment, four indexes are selected to set up the evaluation standard of auto parts remanufacturing scheme. Grey fixed weight clustering method is used to evaluate remanufacturability of the auto parts. Firstly, number index and grey determine the whitenization weight function, then based on the clustering weight of each index, the clustering coefficient matrix is calculated. Finally, the class that certain object belongs to, according to the clustering coefficient matrix is determined.

Findings

Results show that constructed indexes of auto parts remanufacturing scheme can be used for effective evaluation. And the proposed fixed weight grey cluster model can aggregate all indexes information well. Therefore, the proposed indexes and model in this paper are effective and can be used for auto parts remanufacturing.

Practical implications

According to the requirements of the current situation in China, this paper puts forward a method based on grey clustering decision, to evaluate different auto parts remanufacturing schemes, for manufacturing enterprises to provide theoretical basis for remanufacturing production, in order to realize the reasonable configuration of resources.

Originality/value

This paper firstly establishes the evaluation index system of auto parts remanufacturing, the grey clustering theory is introduced into the evaluation of remanufacturing. The fixed-weight grey cluster model is proposed to aggregate indexes’ information.

Details

Grey Systems: Theory and Application, vol. 6 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 9 December 2021

Sifeng Liu, Tao Liu, Wenfeng Yuan and Yingjie Yang

The purpose of this paper is to solve the dilemma in the process of major selection decision-making.

Abstract

Purpose

The purpose of this paper is to solve the dilemma in the process of major selection decision-making.

Design/methodology/approach

Firstly, the group of weight vector with kernel has been defined. Then, the weighted comprehensive clustering coefficient vector was calculated based on the group of weight vector with kernel. Under the action of weighted comprehensive clustering coefficient vector, the information including in other components around component k and supporting object i to be classified into the k-th category has been gathered to component k. At last, a novel two-stage decision model based on the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector is put forward to solve the dilemma in grey clustering evaluation. Then the overall evaluation conclusion can be consistent with the clustering result according to the rule of maximum value.

Findings

A new way to solve the dilemma in the process of major selection decision-making has been found. People can obtain a consistent result with two-stage decision model at the case of dilemma. That is, the conclusion of the overall evaluation is consistent with the clustering result according to the rule of maximum value.

Practical implications

Several functional groups of weight vector with kernel have been put forward. The proposed model can solve the clustering dilemma effectively and produce consistent results. A practical application of decision problem to solve the dilemma in supplier evaluation and selection of a key component of large commercial aircraft C919 have been completed by the novel two-stage decision model.

Originality/value

The two-stage decision model, the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector were presented in this paper firstly. People can solve the dilemma in grey clustering evaluation effectively by the novel two-stage decision model based on the group of weight vector with kernel and the weighted comprehensive clustering coefficient vector.

Article
Publication date: 2 November 2015

Jun Guo, Xi Zhao and Yimin Huang

The purpose of this paper is to establish a grey clustering evaluation model based on center-point triangular whitenization weight function to evaluate the situation of…

Abstract

Purpose

The purpose of this paper is to establish a grey clustering evaluation model based on center-point triangular whitenization weight function to evaluate the situation of urban low-carbon transport development (LTD). The study results intend to provide some theoretical basis and tool support for transport management departments and related researchers who are engaged in low-carbon transport (LT).

Design/methodology/approach

The study uses analytical hierarchy process based on expert investigations to determine the weight of each criteria, classifies the grey clusters based on center-point triangular whitenization weight function, calculates the membership of each development criteria and ranks the development level of all dimensions.

Findings

The research results of case city show that low-carbon technology is in “poor” level, transport facility is in “superior” level, low-carbon policy and environmental coordination is in “intermediate” level, transport management is in “good” level and the overall LTD level is in “intermediate” level.

Practical implications

Reducing the carbon emissions of urban transport and achieving LT is the key to promote urban sustainable development, the scientific judgment of transport development situation is the premise of promoting LTD. Therefore, based on the practices of LT in China, the study systematically clarifies LTD from five dimensions of reflecting LTD.

Originality/value

From the perspective of sustainable development, the evaluation index system of LTD is built with five dimensions consisting of low-carbon technology, low-carbon policy, transport facility, transport management and environmental coordination. Then assess the LTD by using the grey clustering evaluation model based on center-point triangular whitenization weight. This paper presents a new research idea for LTD evaluation.

Details

Grey Systems: Theory and Application, vol. 5 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 17 June 2019

Xiaozhong Tang and Naiming Xie

The purpose of this paper is to construct a grey clustering evaluation model based on center-point mixed possibility function and to evaluate the tourism development…

Abstract

Purpose

The purpose of this paper is to construct a grey clustering evaluation model based on center-point mixed possibility function and to evaluate the tourism development potential of tea intangible cultural heritage. The research results provide a certain reference for the tourism development department and related researchers who are engaged in the tourism development of intangible cultural heritage.

Design/methodology/approach

The study uses literature research, questionnaire investigation, expert interviews and factor analysis to determine the evaluation index system of tourism development potential of tea intangible cultural heritage and applies analytic hierarchy process (AHP) to determine the weight of each criteria. Then, according to the grey clustering evaluation theory and two-stage decision model, a grey clustering evaluation model is constructed to assess the tourism development potential of tea intangible cultural heritage. Finally, a new model is employed to evaluate the tourism development potential of tea intangible cultural heritage in Huangshan city.

Findings

The results show that there is a big difference in the tourism development potential of different tea intangible cultural heritages in Huangshan City and it further illustrates the scientificity and rationality of the method proposed in this paper.

Practical implications

The model constructed in the paper can be effectively applied to the evaluation of tourism development potential of tea intangible cultural heritage scientifically and reasonably.

Originality/value

This manuscript not only constructs the evaluation index system of tourism development potential of tea intangible cultural heritage but also creatively applies the grey clustering theory to the evaluation of tourism development potential of tea intangible cultural heritage, which provides a new research idea for the evaluation of tourism development potential of tea intangible cultural heritage.

Details

Grey Systems: Theory and Application, vol. 9 no. 3
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 26 November 2019

Dang Luo, Manman Zhang and Huihui Zhang

The purpose of this paper is to establish a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities in Henan Province.

Abstract

Purpose

The purpose of this paper is to establish a two-stage grey cloud clustering model to assess the drought risk level of 18 prefecture-level cities in Henan Province.

Design/methodology/approach

The clustering process is divided into two stages. In the first stage, grey cloud clustering coefficient vectors are obtained by grey cloud clustering. In the second stage, with the help of the weight kernel clustering function, the general representation of the weight vector group of kernel clustering is given. And a new coefficient vector of kernel clustering that integrates the support factors of the adjacent components was obtained in this stage. The entropy resolution coefficient of grey cloud clustering coefficient vector is set as the demarcation line of the two stages, and a two-stage grey cloud clustering model, which combines grey and randomness, is proposed.

Findings

This paper demonstrates that 18 cities in Henan Province are divided into five categories, which are in accordance with five drought hazard levels. And the rationality and validity of this model is illustrated by comparing with other methods.

Practical implications

This paper provides a practical and effective new method for drought risk assessment and, then, provides theoretical support for the government and production departments to master drought information and formulate disaster prevention and mitigation measures.

Originality/value

The model in this paper not only solves the problem that the result and the rule of individual subjective judgment are always inconsistent owing to not fully considering the randomness of the possibility function, but also solves the problem that it’s difficult to ascertain the attribution of decision objects, when several components of grey clustering coefficient vector tend to be balanced. It provides a new idea for the development of the grey clustering model. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

Details

Grey Systems: Theory and Application, vol. 10 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 5 February 2018

Bentao Su and Naiming Xie

The purpose of this paper is to construct a grey clustering model based on the nonlinear whitenization weight function and to assess the safety of civil aircraft by using…

Abstract

Purpose

The purpose of this paper is to construct a grey clustering model based on the nonlinear whitenization weight function and to assess the safety of civil aircraft by using a quantitative method.

Design/methodology/approach

According to the running stage of civil aircraft safety assessment issues, first the civil aircraft safety evaluation index system is constructed by using a qualitative method. Taking the information duplication between indicators, the grey relational analysis method is used to filter the key indicators, then the grey clustering evaluation model of nonlinear whitening right function is built to evaluate the safety of civil aircraft and the algorithm steps of the evaluation model are given. Finally, the model is validated by collecting the parameters of nine different civil aircrafts at home and abroad.

Findings

The results show that the safety level of different types of aircraft is different due to the different index parameters, and to some extent, explain the rationality and scientificity of the method proposed in this paper to solve the problem.

Practical implications

This paper gives a complete set of security assessment methods, which can be used to evaluate the security of civil aircraft in the operational phase quantitatively, scientifically and reasonably. Furthermore, it can be extended to other complex system security or stability assessment issues.

Originality/value

It not only provides the supplement and perfection of the safety assessment method in the theoretical system to a certain extent, but also provides a theoretical guidance to solve the problem of civil aircraft system safety assessment of civil aircraft manufacturing enterprise all over the world. At the same time, the nonlinear grey clustering evaluation model constructed in this paper is an improvement of the traditional model, which is, to some extent, the improvement of the grey clustering evaluation theory.

Details

Grey Systems: Theory and Application, vol. 8 no. 1
Type: Research Article
ISSN: 2043-9377

Keywords

Article
Publication date: 22 January 2019

Kejia Chen, Ping Chen, Lixi Yang and Lian Jin

The purpose of this paper is to propose a grey clustering evaluation model based on analytic hierarchy process (AHP) and interval grey number (IGN) to solve the clustering

Abstract

Purpose

The purpose of this paper is to propose a grey clustering evaluation model based on analytic hierarchy process (AHP) and interval grey number (IGN) to solve the clustering evaluation problem with IGNs.

Design/methodology/approach

First, the centre-point triangular whitenisation weight function with real numbers is built, and then by using interval mean function, the whitenisation weight function is extended to IGNs. The weights of evaluation indexes are determined by AHP. Finally, this model is used to evaluate the flight safety of a Chinese airline. The results indicate that the model is effective and reasonable.

Findings

When IGN meets certain conditions, the centre-point triangular whitenisation weight function based on IGN is not multiple-cross and it is normative. It provides a certain standard and basis for obtaining the effective evaluation indexes and determining the scientific evaluation of the grey class.

Originality/value

The traditional grey clustering model is extended to the field of IGN. It can make full use of all the information of the IGN, so the result of the evaluation is more objective and reasonable, which provides supports for solving practical problems.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 12 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 6 August 2018

Fenyi Dong, Bing Qi and Yuyang Jie

The purpose of this paper is to cluster and analyse the level of agricultural science and technology in China’s provinces by using grey clustering model, to have an…

Abstract

Purpose

The purpose of this paper is to cluster and analyse the level of agricultural science and technology in China’s provinces by using grey clustering model, to have an overall understanding of the current situation of agricultural science and technology development in these provinces, and to offer a reference for decision-making departments to draw up agricultural science and technology development plans.

Design/methodology/approach

First of all, the grey clustering assessment is used to evaluate the clustering of agricultural science and technology level in China’s provinces in 2011, 2013 and 2015. Also a comparative static analysis is made. Then, based on the prediction data of GM (1,1) model, the provincial agricultural science and technology levels in 2017 and 2019 are analysed by grey clustering. Finally, some suggestions are put forward, such as adjusting the allocation of agricultural science and technology resources and providing policy preferences to backward areas, so as to promote the coordinated development of agricultural science and technology in China.

Findings

The development of agricultural science and technology in various provinces and regions of the authors’ country is unbalanced, with a big gap of agricultural and technology level between different provinces. What’s more, the level of agricultural science and technology in remote areas has been developing slowly, but it has been lagging behind. Through the grey clustering analysis of the provincial agricultural science and technology level in 2017 and 2019, it is concluded that the level of agricultural science and technology will be promoted as a whole, but the gap of agricultural science and technology level between different provinces and cities will be enlarged.

Research limitations/implications

This paper comprehensively studies the current situation and future development trends of agricultural science and technology in China’s provinces in recent years, and preliminarily analyses the reasons for the transformation of agricultural science and technology level, however, with no further inspection. Related research should be made for further study.

Practical implications

This paper will provide overall understanding of the current situation of agricultural science and technology development in China’s provinces and cities, and put forward relevant suggestions for the future development of agricultural science and technology in China’s provinces and cities, and provide references for decision-making departments to draw up agricultural science and technology development plans.

Originality/value

For the first time, the grey clustering method is used to the research of agricultural science and technology level in the province. It analyses and evaluates the past and present situation and predicts the future development trend of provincial agricultural science and technology level by the grey clustering analysis method, which is a complete research.

Details

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

Keywords

1 – 10 of over 4000