Grey Clustering Method Research Articles

A group decision-making method for technology selection of petrochemical enterprises

Selecting appropriate energy conservation and emission reduction technologies is essential for the sustainable developments of petrochemical enterprises. It usually involves experienced experts from multi-domain and thus can be regarded as a large-scale group decision-making problem. Existing methods assumed that different experts use the same linguistic term set following the same semantics to express their evaluation values, and derived the ranking of alternatives by an indirectly obtained group preference matrix. Such an approach may induce information loss. To avoid these defects, this study introduces a model based on rank centrality and expert differences to choose appropriate technologies for petrochemical enterprises. First, an attitude parameter is introduced into a linguistic scale function to unify different judgment benchmarks of experts regarding the same linguistic term. Next, a direct weight elicitation method based on rank centrality is developed to deduce the individual rank vector of alternatives. A grey clustering method based on the similarities of individual rank vectors is extended to cluster experts into small groups, and the silhouette coefficient is used to determine clusters weights. Afterwards, the rank vectors of alternatives corresponding to subgroups and the global rank vector are calculated by the weighted averaging operator. Alternatives are ranked by the rank vector of the global group. Finally, four technologies were evaluated by the model, and the preferred technology was identified. The findings indicate that the proposed technology selection model alleviates information loss, elevates group consensus level, and provides a perspective for petrochemical enterprises in search of energy conservation and emission reduction technologies.

A maximum satisfaction consensus-based large-scale group decision-making in social network considering limited compromise behavior

With the enrichment of social platforms, large-scale group decision-making (LSGDM) in social networks has gradually taken shape. In practice, experts may show limited compromise behavior during consensus reaching process (CRP), which may lead to bias or even failure in decision-making results. To tackle this issue, considering limited compromise behavior, this paper proposes a maximum satisfaction consensus (MSC) model, and focusing on LSGDM with fuzzy preference relation in social networks. Firstly, an expert weight determination algorithm integrating the interactive weights and individual weights is constructed. The interactive weights are determined by social influence strength, while the individual weights are measured by the compromise degree of limited compromise behavior and the consistency level of preferences. Subsequently, a grey clustering method is developed to classify experts into subgroups, considering both opinions similarity and limited compromise behavior similarity. In CRP, considering the limited compromise behavior, an MSC model under the limited budget determined by the minimum cost consensus (MCC) model is proposed. Based on MSC and MCC models, satisfaction-cost ratio is defined to measure the efficiency of CRP. Finally, a case study of selecting of shared bicycle operators and further discussion are conducted to verify the feasibility and superiority of the study.

Grey Systems Model to Assess Water Quality in Mantaro River in Peru

The section of the Mantaro River that flows through the department of Huancavelica, Peru, has been affected by toxic wastes and mineral residues from industrial and mining activities, which have directly impacted the water quality. In this work, a grey system model, based on the grey clustering method, was used to assess water quality. The grey clustering method was applied using the central point of triangular whitening weight functions (CTWF). In addition, the Prati index and the Environmental Quality Standards for water from the Peru government were revised and used for this study. In the case study, six physicochemical parameters, pH, DO, BOD, Cd, As, and Pb, at nine monitoring points were assessed along the Mantaro River. The results showed that the sixth monitoring point (P6), which is influenced by mining activity, was highly contaminated, while the other points were classified as noncontaminated. Finally, the results obtained by applying the grey clustering method can be useful to competent authorities, for decision making on water management in this watershed.

Grey clustering and grey ranking of bank branches based on grey efficiency

PurposeCompetition in the banking sector is more complex than in the past, and survival has become more difficult than before. The purpose of this paper is to propose a grey methodology for evaluating, clustering and ranking the performance of bank branches with imprecise and uncertain data in order to determine the relative status of each branch.Design/methodology/approachIn this study, the two-stage data envelopment analysis model with grey data is applied to assess the efficiency of bank branches in terms of operations. The result of grey two-stage data envelopment analysis model is a grey number as efficiency value of each branch. In the following, the branches are classified into three grey categories of performance by grey clustering method, and the complete grey ranking of branches are performed using “minimax regret-based approach” and “whitening value rating”.FindingsThe results show that after grey clustering of 22 branches based on grey efficiency value obtained from the grey two-stage DEA model, 6 branches are assigned to “excellent” class, 4 branches to “good” class and 12 branches to “poor” class. Moreover, the results of MRA and whitening value rating models are integrated, and a complete ranking of 22 branches are presented.Practical implicationsGrey clustering of branches based on grey efficiency value can facilitate planning and policy-making for branches so that there is no need to plan separately for each branch. The grey ranking helps the branches find their current position compared to other branches, and the results can be a dashboard to find the best practices for benchmarking.Originality/valueCompared with traditional DEA methods which use deterministic data and consider decision-making units as black boxes, in this research, a grey two-stage DEA model is proposed to evaluate the efficiency of bank branches. Furthermore, grey clustering and grey ranking of efficiency values are used as a novel solution for improving the accuracy of grey two-stage DEA results.

A study on the landscape evaluation of sculpture vignettes in residential areas based on SBE

Abstract Sculpture landscape in urban residential areas plays an important role in creating an urban landscape and is significant in highlighting the urban taste and strengthening urban temperament. This study is based on SBE and the gray clustering method to evaluate the sculptured landscape in residential areas and mainly selects the aesthetic consistency and aesthetic difference data of the surveyed groups for quantitative analysis. In this paper, the sculptures in the residential area of Chengdu city center were used as the main objects for the current situation research and beauty evaluation, and regression analysis was conducted. The study results show that the surveyed groups rated the randomly selected sculpture landscapes on a scale of -1 to 2. The ratings of the selected six dimensions were mainly positive, indicating that the ratings of the beauty of the sculpture landscapes in residential areas were high. The SBE values were all positive, between 0 and 0.5, indicating that the surveyed groups rated these samples more positively and the beauty ratings were better. However, there are still some shortcomings in the residential sculpture landscape, including insufficient post-management, insufficient culture, artistry, diversity, and science popularization, and insufficient cultural symbolism of residential sculpture. Based on the SBE evaluation results, it is of great significance to focus on the post-management of residential sculpture landscape and the construction of urban cultural symbols to construct spiritual civilization and improve environmental quality in cities.

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.

Artificial Intelligence Model Based on Grey Clustering to Access Quality of Industrial Hygiene: A Case Study in Peru

Industrial hygiene is a preventive technique that tries to avoid professional illnesses and damage to health caused by several possible toxic agents. The purpose of this study is to simultaneously analyze different risk factors (body vibration, lighting, heat stress and noise), to obtain an overall risk assessment of these factors and to classify them on a scale of levels of Unacceptable, Not recommended or Acceptable. In this work, an artificial intelligence model based on the grey clustering method was applied to evaluate the quality of industrial hygiene. The grey clustering method was selected, as it enables the integration of objective factors related to hazards present in the workplace with subjective employee evaluations. A case study, in the three warehouses of a beer industry in Peru, was developed. The results obtained showed that the warehouses have an acceptable level of quality. These results could help industries to make decisions about conducting evaluations of the different occupational agents and determine whether the quality of hygiene represents a risk, as well as give certain recommendations with respect to the factors presented.

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.

Research on the Risk Management of Shantytown Renovation Project Based on Grey Clustering Method

In this paper, the risk evaluation model of shantytown transformation is constructed with the second area shantytown transformation project of Q city as a research case. Firstly, the brainstorming method and Delphi method are used to determine the risk evaluation index system of shantytown transformation, secondly, the weights of the evaluation model are determined by a linear combination of the C-OWA operator assignment method and entropy weighting method, which reduces the subjective influence of the assignment, and finally, the grey clustering method is used to assess the risk level of the shantytown transformation, and relevant measures are proposed to reduce the risk of the shantytown transformation according to the results, which reduces to a certain degree the the possibility of risk occurrence in the process of shantytown transformation, providing theoretical guidance for the shantytown transformation project in Q city.

A consensus model for linguistic group decision making considering emotion analysis

In a problem of linguistic group decision-making (GDM), various emotional characteristics of decision-makers’ (DMs) behind their preference series, which is defined as emotion factor, can impact consensus reaching process. As words mean different things to different people, this study comprehensively proposes a novel consensus model with emotion factors based on personalized individual semantics. An improved grey clustering method facilitates to obtain emotion factors. Finally, the proposal model can provide more accurate judgments for moderator's management and further promote consensus.

Soil Quality Assessment from Areas of Great Mining Interest Using the Grey Clustering Method

Mining is one of the most important activities in Peru, although controversial because it is currently highly criticized for generating environmental liabilities that mostly contain a high content of metals which contaminate the different environmental components such as water. , soil, air, biodiversity and social among others, for the study and analysis of the soil in a specific area we will use the grey clustering methodology, which determines, based on the grey systems and it should be noted that for this analysis it was also used as a reference the parameters defined by the Kelley Directives, a clustering coefficient through various calculations and with these define the level of soil contamination in 5 sectors located in the communities of Michiquillay and La Encañada. With the calculated grey clustering coefficients, it was determined that, of the five sectors, only the Michiquillay sector presents a slight level of contamination, and the other sectors are in uncontaminated soils, at least for the parameters that were selected. Mining activity, the authorities in charge of measuring the environmental impact in the sector, can proceed to investigate and infract if the permitted limits are exceeded and these have not been correctly remedied. The results of this study could be an important contribution for the analysis of soil contamination and the impact on the same of future mining projects that are developed in Michiquillay and La Encañada communities studied, how much the natural conditions of the soils have changed after the operation of the mine. Keywords—Grey Clustering, Grey Systems, Mining Activities, Soil Quality.

Optimisation of the Construction Plan of Assembled Concrete Structures in Other Courtyard Buildings Based on Grey Clustering

The assembled concrete structure is a common construction solution in the current building industry, and it is debatable how to further improve the construction efficiency of the pointed claw assembled concrete structure. The study proposes a grey clustering method based on the improved OWA operator as a means to obtain more effective construction evaluation indicators. In performance tests, it was shown that the grey clustering method under the OWA operator optimisation is more capable of computing features for large amounts of data than traditional grey clustering, with an execution time of less than 200s. In the application tests of the construction scheme, the study showed that the proposed optimisation scheme has a more effective safety evaluation, shorter construction period and lower resource consumption. These results show that the use of grey clustering is effective in optimising the construction of assembled concrete structures, and that the optimised solutions show better reduction in construction time and resource utilisation than traditional construction solutions, so that the rational use of grey clustering in assembled buildings will help the construction industry to achieve greater efficiency in construction.

Research on the Beibu Gulf Port Container Terminal Operation System Construction Performance Evaluation Based on the AISM-ANP

With the continuous development of smart ports, the construction of port information systems has become the construction focus of the future development of such ports. However, the existing performance evaluation system for port information systems represents a research gap. It cannot effectively achieve specific improvement in the construction of information systems for port services and capabilities. In this paper, an evaluation index system was forged from the three perspectives of the operating level, management capability, and economic efficiency. As a first step, starting from the current situation of Beibu Gulf Port (Port B) construction, the three dimensions of the evaluation index system were determined using the scheme of literature review, questionnaire research, and fieldwork. Additionally, through adversarial interpretive structural modeling (AISM), it is concluded that the port loading and unloading operation capability and service level are the fundamental factors for measuring the construction performance of the container terminal operation system (CTOS). The results are used as input to construct an analytic network process (ANP) model to obtain the index weights. Finally, the gray clustering method (GCM) is introduced to construct a quantitative evaluation model to quantitatively evaluate the construction performance of the Port B CTOS. The quantitative benefits brought by the construction of the CTOS are finally verified. The scores of the corresponding dimensions of the port before and after the construction of the CTOS system in Beibu Gulf Port are obtained experimentally. The conclusion shows that the construction of CTOS makes the port operating level module improve the most, from 40.023 to 70.733 points; at the same time, it is found that two aspects, i.e., green security and economic benefits, in current construction are directions requiring further work in future port construction. Finally, a visualized quantitative analysis and evaluation method for the performance of smart port construction is proposed.

Assessment and Analysis of Soil Quality in an Industrial Zone from Lima, Peru Using the Grey Clustering Method

Within the district of Ventanilla there are many lead smelting companies, which emit gases containing heavy metals that, when transported to human settlements, could be causing damage to the health of the population, mostly harming young children. At present, the evaluation of soil quality involves the monitoring of various indicators that are analysed independently, leaving aside the systemic approach in which the elements interact and often restrict each other, making the analysis very complex. In this sense, a superior analysis system is proposed based on the Grey Clustering method, which is based on the theory of grey systems, an artificial intelligence approach that allows for an integral evaluation and takes into account the high degree of uncertainty present in the environment. The proposed methodology was used for the study of soil quality in the industrial park of the district of Ventanilla - Mi Perú, specifically in 3 Areas of Potential Interest (API): "Mercado Virgen de Guadalupe", "Patio de La I.E.P. Arturo Padilla Espinoza" and "AA.HH. Las Casuarinas". The results of the evaluation of soil quality using the Grey Clustering method showed that 40% of the total number of monitoring points have very poor soil quality, with the Virgen de Guadalupe Market area having 75% of the monitoring points with very poor soil quality. Finally, the present study can be of great use to the competent authorities related to the surveillance and monitoring of soil quality, as well as the health of the nearby population in order to make decisions on the control of nearby industrial activities.

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.

Applying Grey Clustering Method and Pearson Correlation to Assess Water Quality

The Mantaro River travels through Junín, Ayacucho, and Huancavelica departments,in Peru, and receives not only domestic discharges from the population but also tailings fields and dumps containing lead, silver, copper, and zinc from mining companies. To be able to assess the water quality, the grey clustering method was applied, using Center-point Triangular Whitenization Weight Functions (CTWF) for this purpose. As well, Pearson correlation between parameters was used to understand the dynamics of pollution. In the watershed of the Mantaro river the results of the Monitoring of the Surface Water published in 2018 by the Mantaro Water Administrative Authority were compared to the Peruvian Environmental Quality Standards (ECA) Category 1, subcategory A parameters. The results obtained suggest that the main driver of pollution in the Mantaro river is not mining, but domestic waste in landfills and probably agriculture. Finally, this study shows responsible environmental management by mining companies, besides, could be helpful for regional and local authorities of Peru in making decisions to improve the management of the Mantaro river watershed and make the population aware of the sustainable use of water

The method and its applications of determining possibility function of grey set

PurposeGrey set is the important foundation of the grey mathematics and grey system theory, and the possibility function is the way of expressing grey set. This paper aims to establish the method of determining the possibility function of grey set and discusses its extended applications.Design/methodology/approachFirst, the grey kernel and the grey support set of grey set are defined, and the properties of grey kernel are analyzed. Second, according to the decomposition theorem of grey set, a method of determining the possibility function of grey set is put forward in this paper, which is called the method of increasing information and taking maximum and minimum (IITMM), and then it is further simplified as the method of increasing information and taking maximum (IITM), and an simple example is given to illustrate the calculation procedure. Finally, the grey information cluster method (GICM) based on IITM is proposed and applied to the ecological and geographical environment analysis of pine caterpillar.FindingsThe results show that the grey kernel of grey set still has grey uncertainty; the method of IITM has simple calculation and strict mathematical basis, and it can synthesize the information of the research object and accords with the principle of using minimum information; the GICM and the fuzzy cluster method have the same classification effect.Practical implicationsThe researches show that method of IITM can be used not only to determine the possibility function of the grey set effectively, but also be used for the evaluation and cluster analysis of connotative objects. The classification result of the GICM presented in this paper is more precise than that of the fuzzy cluster method.Originality/valueThe paper succeeds in realizing both the IITM method for determining the possibility function of grey set and the GICM based on IITM for the connotative objects.

The Evaluation Method of Community Emergency Resource Allocation Based on Coordination Sensor Information Collection

This paper analyzes the information collection data of coordination sensors and designs a corresponding evaluation method to conduct an in-depth assessment of the configuration of community emergency resources. Based on the principles of assessment index system construction and the actual research, an assessment index system of community emergency resource allocation level is established. In this paper, the G1 method was selected to determine the weights of the evaluation indexes, and the gray clustering method was applied to construct the whitening weight function, determine the gray level to which each index belongs and the affiliation degree of each gray class, and establish a comprehensive evaluation model of the community emergency resource allocation level. In response to the problem that the increase of state variables leads to a decrease in real-time map building, a dynamic local window size mechanism is proposed, which can reduce the time consumption and save computational resources under the condition of ensuring the accuracy of positioning and map building. Therefore, it is urgent to design an efficient self-interference cancellation mechanism to resist the influence of self-interference on the signal-to-noise ratio of the first-hop link. For example, the IMU pre integration theory is combined with the wheel range method to solve the problem of frequency synchronization; An initialization algorithm is proposed to recover the scale information of the camera and optimize the external parameters; Design a graphic optimization framework integrating IMU, wheel range finder and camera. The monitoring terminal sends the data information of coordination transportation to the monitoring platform in real-time, and the monitoring platform is responsible for storing and displaying the data information, thus realizing the real-time monitoring of the coordination transportation process. Finally, the functions of the monitoring terminal and the display system of the monitoring platform experiment, respectively, and the test results verify the effectiveness and integrity of the system data communication, which proves the correctness of the terminal design of the integrated coordination monitoring system based on multidimensional information and has practical engineering value.

Complexity Reduction for the Architecture Design of Large-Scale Public Buildings Based on Seismic Structure Simulation Technology

In order to improve the seismic effect of large-scale public building architecture design, this paper studies the large-scale public building architecture design with the support of seismic structure simulation technology and improves the large-scale public building architecture design effect through simulation research. Furthermore, on the basis of the construction of the seismic performance evaluation system and the determination of the index weight, this paper assigns the index data to the sample table of the seismic performance checklist and establishes the seismic performance evaluation model based on the gray fixed-weight clustering method. Furthermore, using the seismic structure modeling technique described in this study, this paper assesses the seismic performance of public buildings. Finally, through experimental research, this paper verifies that the design method of large-scale public building architecture based on seismic structure simulation technology has certain practical effects.

Algorithm Based on Grey Clustering and Shannon Entropy to Assess Landscape Visual Quality

Landscape assessment has been limited to methodologies with subjective and qualitative approaches, due to prevailing the concept of landscape as the perception of territory. In this work, the intrinsic visual quality of the landscape was evaluated using an algorithm based on grey clustering and Shannon entropy. The grey clustering method was used to determine the landscape visual quality, and Shannon entropy was applied to calculate wights of criteria used for evaluation. The case study was performed on mining project located in Cajamarca, Peru, where three landscape units were identified and four evaluation criteria were established, before and after the implementation of project. The results revealed that there is a notable effect of the change in landscape visual quality in three evaluated landscapes units. The criteria in order of evaluation were the intrinsic visual quality of the water, relief, vegetation cover, and artificial elements. Consequently, the method showed quantitative and qualitative results that could help the landscape assessment process to make better decisions regarding mining projects. Keywords—Grey clustering, Landscape visual quality, Mining project, Shannon entropy.