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The Distinguishing Coefficient (ξ) is an important parameter of Grey Relational Analysis (GRA), a flagship multi-criteria decision making (MCDM) model of Grey System Theory, an intelligent and multifaceted field developed by Chinese scientists in 1980s. However, the scholars widely assume ξ = 0.5. The current study questions this practice. Also, some scholars have argued that the variation in ξ doesn't influence the ranking of the factors through GRA. On contrary, the study demonstrates, the variation in ξ can influence the ranking. This has been shown through a case involving primary data concerning the perceived relative importance of Project Management Knowledge Areas (PMKAs). This study is significant for the analysts of uncertain systems, represented by grey or fuzzy systems, who intend to use GRA for intelligent multi-criteria decision making. It encourages ξ - driven sensitivity analysis of GRA model before interpreting the results. The study reveals, by tailoring the value of ξ a point can be achieved where the ranking obtained through GRA can be made most comparable to the other MCDM methods. For comparative analysis of the GRA based results the study deployed three other MCDM techniques; Analytic Hierarchy Process, Best Worst Method and Simple Additive Weighting. [ABSTRACT FROM AUTHOR]

Considering the varying levels of disability among elderly people, the capability layer → demand layer → service layer structure was decomposed step by step. This enabled us to establish a quality house model that forges an association matrix between care needs and care service attributes for disabled elderly individuals residing in the community. Considering the decision maker's expected grey target and irrational risk attitude towards care service attributes, the prospect-grey target house care service quality evaluation model for disabled elderly individuals in the community was constructed based on prospect theory and grey target decision-making. By evaluating the quality of care services for disabled elderly individuals in the community, the care service levels of different types of disabled elderly individuals and groups that require improvements in care services were identified. [ABSTRACT FROM AUTHOR]

To analyze the properties and functions of different weakening buffer operators of AWBO, GAWBO and FB-WBO, some data series and their operator-buffered series are converted from time domain to frequency domain using Fourier transformation. Base on the spectrum analysis of the time series in frequency domain, the properties and functions of different weakening buffer operators of AWBO, GAWBO and FB-WBO are obtained At the low frequency part, the spectrum amplitude of the weakening operators of AWBO and GAWBO buffered series is higher than the original data sequence. At the high frequency part, compared to the original data sequence, the weakening operators of AWBO and GAWBO buffered series has attenuation effect. For a general data series, the buffer operators of FB-WBO with different fractional order have attenuation effect to the spectrum of original data series at most or all frequency contents. But for the data series with violent oscillations, the buffer operators of FB-WBO with different fractional order do not help to reduce the data oscillations. [ABSTRACT FROM AUTHOR]

In the real life, it has the obvious characteristic of multiple uncertainties for most of the data which are obtained. The multiple uncertainties appear as that the data have fuzziness, greyness and randomness meanwhile. However, there are limitations to research on the clustering of multiple uncertain data with the present uncertain multi-attributes clustering decision-making method. To solve the clustering problems of the multiple uncertain data, the concept and proof process of generalized interval grey numbers is proposed by analyzing the relationship of grey number, fuzzy number, Interval-valued fuzzy number and probability number. According to generalized interval grey number, its possibility function is inferred by extending the traditional grey possibility function. Then the variable weight clustering model of generalized interval grey numbers is proposed to research on the clustering problems of the multiple uncertain data. The results of the application example show that the model proposed is effective to solve this kind of clustering problems. [ABSTRACT FROM AUTHOR]

The traditional possibility functions are always assumed to be linear functions. The preferences of decision-makers are not considered. It might not be proper to analyze all kinds of indicators with the traditional possibility functions. Therefore, we consider the preferences and first develop the universal possibility functions. The decision-makers can obtain the appropriate universal possibility functions by adjusting the clustering preference. Then, the related properties are revealed by the proof. Next, grey clustering methods with universal possibility functions are proposed. Finally, the effectiveness of the suggested methods is verified via the case illustration and comparative analysis. [ABSTRACT FROM AUTHOR]

With the continuous development of the telecom industry, telecom operators can provide more and more diversified services for customers. But at the same time, the customers' requirements of service are also constantly improving. So how to make full use of customers' data to provide better service for customers has become the main work of operators and the main problem which need to be solved. This paper mainly solve the problem of customers clustering, and propose an ensemble customer clustering model--GIKM clustering model which based on grey incidence and KMeans: Using grey clustering method, by comparing the grey absolute incidence degree between indexes with the preset critical value to finish the indexes simplification, through this we can solve the problem that traditional method existed, such as: existing many subjective factors, requiring large amount of calculation. Then, using K-Means method to cluster the simplified customers 'data, and according to the clustering result and the main characteristics of all kinds of customers to propose some suggestion about strategy. Finally, the present situation and the development prospection of telecom customers clustering analysis are summarized. [ABSTRACT FROM AUTHOR]

Considering the uncertainty of environment and a lot of grey information in the cooperation of strategic emerging industrial clusters and based on the relative theory of interval grey number, a multi-weighted Shapley value model with interval grey payment is constructed. Furthermore, information entropy model is used to revise the weight in the multi-weighted Shapley value model, which involves five factors of assets investment,the number of R & D personnel and number of patents, knowledge exchange ability and anti-risk ability. Finally, the feasibility, rationality, and fairness of the improved multi weight Shapley model are proved by an example. [ABSTRACT FROM AUTHOR]

To address the unreasonable matching of care service resources for disabled elderly individuals in the conununity, we first identified uncertainties in the expression of care needs by disabled elderly individuals and their flimilies and the expression of care service resources by care institutions, declined the matching of the supply and demand of care service resources for disabled elderly individuals, and explored the expected demand evaluation values of different types of disabled elderly individuals and care service institutions. A grey bilateral matching model for care service resources in the case of incomplete supply and demand information was then constructed by considering the different degrees of disability of disabled elderly individuals, extending from the original one-to-one matching model to a one-to-many matching model. Finally. MATLAB simulation was used to obtain the optimal match between disabled elderly individuals and care service institutions, thereby providing an accurate and efficient niatch between the supply and demand of care service resources. [ABSTRACT FROM AUTHOR]

With limited cognition, the group of players can only estimate the range of their payoffs instead of the specific values. Then we propose the asymmetric grey evolutionary game. Via the analysis of the equilibrium of this game, the single grey belt and crossed grey belt are found. Meanwhile, besides Nash equilibrium, we find a new equilibrium. When the group of players are in the crossed grey belt, they can't obtain more profits no matter how they change the original strategies. Because their grey expected profits are always equal to the grey average expected profits. This is a short-term equilibrium due to limited cognition. Finally, we illustrate the asymmetric grey evolutionary game to analyze the effect of psychological contract breaches on employee turnover intention. [ABSTRACT FROM AUTHOR]

This paper realizes the rapid development of the MATLAB of grey prediction models through public module call. Firstly, the multiple modeling steps of grey prediclion models are divided into three types: Model, View, and Controller. Then, it is analyzed which steps are completely common to all models. Finally, these steps are encapsulated into general modules similar to JavaBean. These modules can be called program building blocks for compiling grey prediction modeling software. which greatly improves the development elliciency, reduces code redlindancy, and improves the stability ofilie software. This is of great ralite to the popularization of grey prediction models. [ABSTRACT FROM AUTHOR]

Various forecasting models have been developed to reveal the real world in a better way. The GM(1,1) model is used to forecast the observations or statistical data which deviate from the true values of the actual system because of disturbances and errors. The model is quite useful in the small sample forecasting. However, each forecasting model has its own application condition. Although there had been some researches on the accuracy and applicable conditions of grey models, these researches mainly focused on model performance for specific case. In this paper, a random simulation method for the accuracy test of GM(1,1) was proposed. The results of the random simulation and some real cases demonstrate that the small sample usually has more accuracy than the large sample when establishing grey model in theory. [ABSTRACT FROM AUTHOR]

When building a prediction model, practical experience or real production conditions may produce some constraints for the parameters to be estimated, thus considering this fact, a novel multi-variable grey prediction model GMC(1,N) with the inequality constraints from practical experience or real production condition has been presented, along with the solving algorithm, in this paper. Later, a numerical example of product quality cost analysis was presented to check the effectiveness and feasibility of the proposed method. The case had shown that the Mean Squared Error (MSE) of GMC(1,N) model was usually greater than that of GM(1,N) model, making GMC(1,N) model suitable for reliable practical predictions. [ABSTRACT FROM AUTHOR]