Grey Clustering Evaluation Research Articles

Grey comprehensive evaluation of development performance of provinces in China based on spatiotemporal probability function and variable weight strategy

In the new stage of promoting high-quality economic development, the effect of the transformation of development momentum and the ability of sustainable development has become the key factors for the competitiveness of provinces in China. Especially in the context of the impact of COVID-19 and the obstacles of world trade protectionism, the sustainability of development performance is increasingly important. In the past, when evaluating the development performance of various provinces in China, a single index weight was usually used. In view of evaluation criteria, the lack of consideration of regional differentiation factors would result in the evaluation results deviating from reality. This paper introduces the entropy weight method to determine the weight of regional indicators of differentiated development. Based on the space-time probability function, a grey clustering evaluation model of regional development performance is constructed to conduct a comprehensive grey evaluation of the development performance of various provinces in China from 2009 to 2019. It is found that the new evaluation model can correct the deficiencies of similar probability functions and single index weight and obtain more accurate evaluation results. It’s found that the development performance evaluation results of each province are always in a dynamic adjustment process, which needs to be verified with the help of subsequent expansion analysis.

Research on the Mechanism of Enhancing Informatization Teaching Ability of College Teachers Based on Gray Clustering Evaluation Model

Abstract This paper constructs a gray clustering assessment model, combines the indicators of information technology literacy, technology-supported learning, and information technology teaching ability to evaluate the information technology teaching ability of A college teachers, and explores the use of information technology equipment of college teachers. And through the construction and calculation of the whitening weight function to refine the classification of college teachers’ informatization teaching ability, for different categories of teachers’ informatization application presenting different characteristics, using one-way ANOVA and adding the Scheffe (C) test to test the inter-group variability of different categories, in-depth exploration of the influencing factors of teachers’ informatization teaching in different categories. The results show that the overall water mean of teachers’ informatization teaching ability in school A is 3.88±0.59, and the model divides teachers’ informatization teaching level in college A into three categories: 3.8-4.5, 3-3.8, and 1-3, with the proportion of each category being 27.8%, 40.1%, and 32.1%, respectively. This study focuses on analyzing the relevant factors affecting teachers’ informatization teaching ability and puts forward countermeasure suggestions according to local conditions, which is of great significance to deepen the reform of education and teaching.

Extension Cloud Model and Grey Clustering Evaluation of Enterprise Safety Management System: Based on COWA-CRITIC Combination Weighting

In order to address the issues of unclear risk grading control, lack of safety management, and hidden danger investigation and management processes, this paper used a mining enterprise as the backdrop for an engineering example. The “evaluation model of the overall construction level of the enterprise safety management system” is constructed from four aspects: “preliminary infrastructure”, “risk grading and control”, “hidden danger investigation and management processes”, and “Post-support work”. The safety evaluation level is divided into five levels, and the evaluation model is combined weighted by using the combined ordered weighted averaging (COWA) algorithm and the criteria importance through intercriteria correlation (CRITIC) method. In addition, the cloud model, the extension cloud model, and the grey clustering evaluation method are used for a thorough evaluation. Finally, the enterprise safety management system’s overall construction level is determined to be good. In order to effectively strengthen the enterprise safety management capability and prevent the occurrence of production safety accidents, this study provides a practical and thorough evaluation method for the evaluation of the enterprise safety management system. This method makes it easier to identify system weaknesses and provides a safety guarantee for the sustainable development of enterprises.

Multi-stage skewed grey cloud clustering model and its application

PurposeThe possibility function-based grey clustering model has evolved into a complete approach for dealing with uncertainty evaluation problems. Existing models still have problems with the choice dilemma of the maximum criteria and instances when the possibility function may not accurately capture the data's randomness. This study aims to propose a multi-stage skewed grey cloud clustering model that blends grey and randomness to overcome these problems.Design/methodology/approachFirst, the skewed grey cloud possibility (SGCP) function is defined, and its digital characteristics demonstrate that a normal cloud is a particular instance of a skewed cloud. Second, the border of the decision paradox of the maximum criterion is established. Third, using the skewed grey cloud kernel weight (SGCKW) transformation as a tool, the multi-stage skewed grey cloud clustering coefficient (SGCCC) vector is calculated and research items are clustered according to this multi-stage SGCCC vector with overall features. Finally, the multi-stage skewed grey cloud clustering model's solution steps are then provided.FindingsThe results of applying the model to the assessment of college students' capacity for innovation and entrepreneurship revealed that, in comparison to the traditional grey clustering model and the two-stage grey cloud clustering evaluation model, the proposed model's clustering results have higher identification and stability, which partially resolves the decision paradox of the maximum criterion.Originality/valueCompared with current models, the proposed model in this study can dynamically depict the clustering process through multi-stage clustering, ensuring the stability and integrity of the clustering results and advancing grey system theory.

Retracted: An Analysis of Computer-Aided Design Software Course Teaching in Visual Communication Design Major by Integrating Grey Variable Weight Clustering Evaluation Model

Retracted: An Analysis of Computer-Aided Design Software Course Teaching in Visual Communication Design Major by Integrating Grey Variable Weight Clustering Evaluation Model

A Novel Method of Teaching Quality Monitoring and Evaluation from the Perspective of Educational Balance

Exploring the problem of teaching quality monitoring and evaluation from the perspective of educational balance can help educators and policy makers discover educational inequality problems, thereby promoting fair allocation of educational resources and opportunities. In light of this, this study attempts to research teaching quality monitoring and evaluation from the perspective of educational balance. At first, the mechanism of promoting educational balance by information technology was expounded, and the principle and necessity of a comprehensive assessment based on the evaluation results of different evaluators were explained. Then, this study innovatively introduced the whitening weight function (WWF)-grey evaluation model into the conventional grey clustering evaluation, calculated the unit comprehensive clustering coefficients of the indexes of teaching quality evaluation from the perspective of educational balance, and gave fair, accurate, and effective evaluations. After that, the grey GM (1,1) model was applied to the prediction of teaching quality improvement effect, the future trend of teaching quality changes was predicted based on history data, and the results provided references for teaching reform and educational decision-making. At last, experimental results verified the validity of the proposed method.

Industrial ecological evaluation based on DPSIR and panel grey clustering model

PurposeThis paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological environment in the Yangtze River Economic Belt of China. The purpose of this study is to provide some theoretical basis and tool support for management departments and relevant researchers engaged in industrial sustainable development.Design/methodology/approachThis study uses the driving force pressure state impact response analysis framework to build a comprehensive evaluation index system. Based on the center point triangle whitening weight function, it classifies the panel grey clustering of improvement time and index weight.FindingsThe results show that there are great differences in the level of industrial ecological development in different regions of the Yangtze River Economic Belt, which further illustrates the scientificity and rationality of the evaluation method proposed in this paper.Practical implicationsDue to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. The improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.Social implicationsDue to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. In order to improve the effectiveness of industrial ecological evaluation, the improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.Originality/valuethe new model proposed in this paper complements and improves the grey clustering analysis theory of panel data, that is, aiming at the subjective limitation of using time degree to determine time weight in panel grey clustering, a comprehensive theoretical method for determining time weight is creatively proposed. Combining the DPSIR (Driving force-Pressure-State-Influence-Response) model model with ecological development, a comprehensive evaluation model is constructed to make the evaluation results more authentic and comprehensive.

Two-stage grey cloud clustering model under the panel data and its application

PurposeThe purpose of this paper is to establish a two-stage grey cloud clustering model under the panel data for the multi-attribute clustering problem with three-parameter interval grey number to evaluation of agricultural drought resistance grade of 18 cities in Henan Province.Design/methodology/approachThe clustering process is divided into two stages. In the first stage: Combining variance and time degree, the time weight optimization model is established. Applying the prospect theory, the index weight optimization model is established. Then, with the help of grey possibility function, the first stage of grey cloud clustering evaluation is carried out. In the second stage: the weight vector group of kernel clustering is constructed, and the grey class of the object is determined. A two-stage grey cloud clustering model under the panel data for the multi-attribute clustering problem is proposed.FindingsThis paper indicates that 18 cities in Henan Province are divided into four categories. The drought capacity in Henan province is high in the east and low in the west, high in the south and low in the north and the central region is relatively stable. The drought is greatly affected by natural factors. And the rationality and validity of this model is illustrated by comparing with other methods.Practical implicationsThis paper provides a practical method for drought resistance assessment, and provides theoretical support for farmers to grasp the drought information timely and improve the drought resistance ability.Originality/valueThe model in this paper solves the situation of ambiguity and randomness to some extent with the help of grey cloud possibility function. Moreover, the time weight of time degree and variance are used to reduce the volatility and the degree of subjective empowerment. Considering the risk attitude of the decision makers, the prospect theory is applied to make the index weight more objective. The rationality and validity of the model are illustrated by taking 18 cities in Henan Province as examples.

Comprehensive evaluation method of rural ecotourism based on grey clustering

With the gradual urbanization of the countryside, people’s lifestyles have also undergone tremendous changes. Most people tend to live in the countryside, and people also choose tourist attractions with a rural flavor when traveling. This social background continues to promote the development of rural eco-tourism. develop. While the development of rural eco-tourism is driven by the dividends of the times, it may also be affected by various factors and lead to operational difficulties. In order to keep rural eco-tourism scenic spots in a profitable state, a comprehensive evaluation of rural eco-tourism has become the focus. The method of comprehensive evaluation of rural ecotourism is mainly completed by combining AI algorithms, big data and other auxiliary tools. However, due to the variety of evaluation-related factors involved in the comprehensive evaluation of rural ecotourism, the above evaluation methods cannot fully take into account the rural areas. All aspects of the comprehensive evaluation of ecotourism, so it is necessary to use a method that can complete an effective comprehensive evaluation with less evaluation-related factors to conduct a real evaluation of rural ecotourism. The grey clustering evaluation model is an evaluation method evolved on the basis of the research of Chinese scholars. It can classify and predict the categories according to some characteristics of the clustered objects, which effectively solves the inaccuracy and considerations existing in various current evaluation methods. Incomplete situation. This paper firstly sorts out the grey clustering method and related concepts and theories of rural ecotourism data. After a detailed analysis, and then combined with the gray clustering model to improve the algorithm, an evaluation method with better performance than the traditional gray clustering method was designed. It is found that the improved grey clustering method has more advantages than the method of AI algorithm, big data algorithm and other auxiliary tools for comprehensive evaluation of rural ecotourism.

Measuring the efficiency of public hospitals: A multistage data envelopment analysis in Fujian Province, China.

The present study aimed to evaluate the operational efficiency of public hospitals in Fujian Province and the factors responsible for the inefficiency of these hospitals and provide relevant suggestions for health policymakers in allocating service resources. In the first stage of the research, the variables affecting the efficiency of hospitals were extracted by qualitative and quantitative methods, including literature optimization, gray related analysis and gray clustering evaluation. In the second stage, the data envelopment analysis (DEA) method was used to evaluate the operational efficiency of 49 hospitals of different levels and types selected by sampling in 2020. Finally, a Tobit regression model with introduced institutional factors and background factors was established to study the main influencing factors of hospital inefficiency. In the first stage, 10 input variables and 10 output variables necessary from the mangers' point of view were identified to test efficiency. In the second stage, the average comprehensive TE, PTE, and SE of 49 sample hospitals was 0.802, 0.888, and 0.902, respectively. 22.45% of these hospitals met the effective criteria, i.e., the overall effective rate was 22.45%. The low SE value of the hospital was the main reason hindering the improvement of the comprehensive efficiency value. The overall effective rate of secondary public hospitals (30.77%) was higher than that of tertiary public hospitals (19.44%), and the overall effective rate of public specialized hospitals (30%) was higher than that of general public hospitals (18.92%). Based on the third stage results, the bed occupancy rate (BOR) and the proportion of beds (POB) were major factors affecting the operation efficiency of grade III hospitals (p < 0.01). However, the operating efficiency of grade II hospitals was significantly affected by POB and regional per capita GDP(GDPPC) (p < 0.05). Moreover, the impact of BOR and GDPPC was positive, and POB was negatively correlated with hospital operation efficiency. The study results indicated that the overall operation efficiency of public hospitals in Fujian Province is low. This study revealed that intervention should be strengthened from a policy and management perspective to improve the operation efficiency of public hospitals.

GERT-Q-learning model for intelligent QoS dynamic optimization of Inmarsat STN based on grey clustering of delay and delay variation

PurposeThis paper aims to implement quality of service(QoS) dynamic optimization for the integrated satellite-terrestrial network(STN) of the fifth-generation Inmarsat system(Inmarsat-5).Design/methodology/approachThe structure and operational logic of Inmarsat-5 STN are introduced to build the graphic evaluation and review technique(GERT) model. Thus, the equivalent network QoS metrics can be derived from the analytical algorithm of GERT. The center–point mixed possibility functions of average delay and delay variation are constructed considering users' experiences. Then, the grey clustering evaluation of link QoS is obtained combined with the two-stage decision model to give suitable rewards for the agent of GERT-Q-learning, which realizes the intelligent optimization mechanism under real-time monitoring data.FindingsA case study based on five time periods of monitoring data verifies the adaptability of the proposed method. On the one hand, grey clustering based on possibility function enables a more effective measurement of link QoS from the users' perspective. On the other hand, the method comparison intuitively shows that the proposed method performs better.Originality/valueWith the development trend of integrated communication, STN has become an important research object in satellite communications. This paper establishes a modular and extensible optimization framework whose loose coupling structure and flexibility facilitate management and development. The grey-clustering-based GERT-Q-Learning model has the potential to maximize design and application benefits of STN throughout its life cycle.

A Method of Power Supply Health State Estimation Based on Grey Clustering and Fuzzy Comprehensive Evaluation

Health state estimation can evaluate the current degradation state of equipment, and the evaluation results can provide a basis for formulating equipment maintenance strategies. At present, in the research on health state estimation, only one level of indicators of the equipment is usually considered, meaning incomplete estimation results. In addition, the current evaluation methods rarely consider the impact of data noise on the evaluation results, which can easily lead to abnormal evaluation results. To solve the above two problems, this paper first introduces the state indicators such as ripple voltage and output voltage, as well as the ratio of theoretical use time into the evaluation indicators. Furthermore, a health state estimation method combining grey clustering and fuzzy comprehensive evaluation methods is established. This method can consider the characteristics of multiple data groups at the same time, thus the impact of data noise on the evaluation results can be reduced. During the evaluation, the grey clustering method is used to evaluate the clustering coefficient vector of the power supply under a single group of data. After that, the clustering coefficient vector of multiple groups of data is used as the membership vector of fuzzy comprehensive evaluation, and the fuzzy comprehensive evaluation method is used to evaluate the health state of a power supply under multiple groups of data. An example shows that this method is effective in estimating the health state of a normally degraded power supply.

Higher education evaluation system based on grey clustering evaluation model

Higher education evaluation system based on grey clustering evaluation model

Fuzzy gray clustering evaluation of green building operation effect: a case study of Shenzhen Bay One, China

PurposeThis paper improves the evaluation index system of green building operation effect and establishes the evaluation model of green building operation effect. It is expected to promote energy saving and emission reduction and provide a more scientific evaluation method for green building operation effect evaluation.Design/methodology/approachFirst, 20 key evaluation indexes are selected to establish the operation effective evaluation index system. Then, the combined weight method is proposed to determine the weight of each evaluation index. Next, the gray clustering-fuzzy comprehensive evaluation method is used to construct the green building operation effective evaluation model. Finally, the feasibility and validity of the selected model were verified by taking Shenzhen Bay One green building in Shenzhen as an example.FindingsThis paper establishes the evaluation system of green building operational effect, and evaluates green building from the angle of operational effect. Taking Shenzhen Bay One project as an example, the rationality and applicability of the model are verified.Originality/valueIn this paper, for the first time, relevant indexes of user experience are included in the evaluation system of green building operational effect, which makes the evaluation system more perfect. In addition, a more scientific fuzzy gray clustering method is used to evaluate the operational effect of green building, and a new evaluation model is established.

Multiobjective Optimization Design of Green Building Energy Consumption Based on Inorganic Thermal Insulation Nanomaterials.

In order to solve the problem that building engineering construction needs to consume a lot of energy and cause environmental pollution, which will pose a great pressure on urban resources and environment, this paper proposes that, in building engineering construction, appropriate green construction technology must be selected in combination with the actual situation, so as to effectively reduce the energy consumption of building engineering and improve the use efficiency of building engineering. Firstly, good thermal insulation nanomaterials are selected, which are cost-effective, safe, and nontoxic and has small thermal conductivity, large heat storage coefficient, stable chemical performance, and good construction performance. Secondly, it also needs to be selected according to the actual service life of the building. Because the current evaluation system is mostly aimed at the planning and design stage, and the structure occupies a large part in the building, for example, the impact on the construction period accounts for more than 50% and the impact on the cost accounts for 35%. Therefore, Duan Xiaorong and others established the grey cluster evaluation model of green building structure design based on the triangular whitening weight function. Finally, according to the relevant national regulations, this paper optimizes the design of green buildings based on the basic principles of energy conservation and emission reduction, high quality, and high efficiency.

Grey Clustering Evaluation of Prefabricated Building Construction Safety Based on Anp

Starting from the four common types of safety accidents at the construction site of prefabricated buildings, the theory of cause of accidents is used to discover the main causes of accidents, and the construction safety evaluation indicators are extracted from them and the safety risk evaluation index system is constructed. Then combined with the application of network level analysis and mixed central point triangle whitening weight function to build a model that can evaluate the safety risk of prefabricated building construction. Finally, the model is tested with examples, and factors in an unsafe state are identified and suggestions are made. Provide models and references for the safety management of prefabricated construction sites, thereby reducing safety accidents on the construction site.

Gyro Test Evaluation Based on Grey Clustering

Abstract Based on the test and evaluation of satellite control sub-systems, this article applies the gray clustering evaluation method in the gray system theory to the lack of objective quantitative standards in the current test and evaluation, and establishes the evaluation index system and evaluation model of the two-float gyro. The model is verified by using telemetry data and the evaluation conclusion of the gyro is got. The establishment of the model provides an objective and quantitative standard for the evaluation, and reduces the subjectivity and ambiguity in the evaluation. The model and method can be applied to other components of the control sub-system, and it has promotion significance for the test and evaluation of the entire control sub-system.

Risk Area Identification Model of Bus Bay Stops Based on Distribution of Conflicts

Effective identification of the risk area of the bus bay stop is a prerequisite for the enhancement of traffic safety. This study proposes a method of identifying the risk area based on the distribution of traffic conflicts. Firstly, the traffic flow data of the bus stop is collected by drones and video recognition software, and the traffic flow characteristics of the bus stop are analyzed by the mathematical and statistical methods. Secondly, using the gray clustering evaluation theory, on the basis of the rasterization of the functional area of the bus bay stop, a risk level model based on the index system of conflict rate, conflict severity, and potential conflict risk is proposed. Finally, take a bus stop in Guangzhou as an example to verify the solution. The results show that the constructed model can effectively identify the risk areas of bus bay stops. The risk areas of the bus bay stops are concentrated in the middle and lower reaches of the bus stop, which proves that the impact of bus exiting the stop on the surrounding traffic is greater than the process of bus entering the stop; the traffic risk areas of lanes near the bus stop are concentrated, and the severity of conflicts is low. The traffic risk zone of the lane far away from the bus stop is widely distributed, and the severity of conflict is higher. The research results can provide a basis for the micro safety performance evaluation and safety optimization of bus bay stops, which has strong theoretical and practical significance.

Performance Evaluation Model of Public Resource Trading Platform Using Entropy-Based Gray Clustering Method

In order to standardize public resource trading activities and improve the operating efficiency of public resource trading platforms, this paper conducts research on the performance of public resource trading platforms. A three-level and 28-dimension performance evaluation index system for public resource trading platform is established by considering the four levels of “input-process-output-effect.” Besides, entropy weight method, gray clustering, and fuzzy comprehensive evaluation are integrated on this basis. Entropy weight method is used to determine the index weight, and the degree value of membership for indexes on gray class is determined based on gray clustering method and converted into a matrix. Then, fuzzy comprehensive evaluation method is used to determine the evaluation value and finally carry out the platform performance evaluation, which provides theoretical support for academic researchers to conduct follow-up research on the performance evaluation of public resource trading platforms.

Solving the dilemma in supplier selection by the group of weight vector with kernel

PurposeThe purpose of this paper is to solve the dilemma in the process of major selection decision-making.Design/methodology/approachFirstly, 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.FindingsA 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 implicationsSeveral 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/valueThe 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.