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Numerous countries are implementing building-integrated photovoltaic (BIPV) technology to enhance the energy performance of buildings, as new energy sources have attracted global interest. BIPV residential programs are an essential method to alleviate energy stress and promote energy transition in buildings; however, the high level of technology and capital investment required have hampered their marketization. Although certain obstacles have been examined by researchers, there remains a lack of studies concerning risk assessment in the context of the development of BIPV residential projects. Therefore, this study strives to develop a risk assessment model for the development of these projects. First, a risk evaluation index system is proposed by identifying and analyzing the risks associated with the development of BIPV residential projects, following the lines of risk identification–risk analysis–risk evaluation–risk management. Second, the DEMATEL-ANP-gray cluster analysis was utilized to construct the development risk assessment model. Finally, a case study demonstrates that the methodology proposed in this study can effectively solve the issues associated with correlating risk factors and the quantification of the magnitude of risks in the development of BIPV residential projects. This study will serve as a valuable reference for architect-urban developers and engineer contractors to formulate risk governance countermeasures for BIPV residential projects as it provides a framework for assessing the risk associated with their development. [ABSTRACT FROM AUTHOR]

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Numerous countries are implementing building-integrated photovoltaic (BIPV) technology to enhance the energy performance of buildings, as new energy sources have attracted global interest. BIPV residential programs are an essential method to alleviate energy stress and promote energy transition in buildings; however, the high level of technology and capital investment required have hampered their marketization. Although certain obstacles have been examined by researchers, there remains a lack of studies concerning risk assessment in the context of the development of BIPV residential projects. Therefore, this study strives to develop a risk assessment model for the development of these projects. First, a risk evaluation index system is proposed by identifying and analyzing the risks associated with the development of BIPV residential projects, following the lines of risk identification–risk analysis–risk evaluation–risk management. Second, the DEMATEL-ANP-gray cluster analysis was utilized to construct the development risk assessment model. Finally, a case study demonstrates that the methodology proposed in this study can effectively solve the issues associated with correlating risk factors and the quantification of the magnitude of risks in the development of BIPV residential projects. This study will serve as a valuable reference for architect-urban developers and engineer contractors to formulate risk governance countermeasures for BIPV residential projects as it provides a framework for assessing the risk associated with their development.

The intelligent development of smart industrial parks (SIPs) can not only promote the development of smart cities, but also promote the development of intelligent large-scale buildings. China is strengthening the construction of SIPs; however, the development of SIPs is limited. Due to different understandings of SIPs, the intelligence level of each SIP varies greatly. It is necessary to develop a SIP intelligence level assessment model to check these limitations. Most of the existing evaluations focus on the qualitative evaluation of the overall intelligence level of SIPs, ignoring the influence of each individual dimension. Therefore, this study used quantitative methods to measure the intelligence level of SIPs from the overall and dimensional levels. The evaluation method included five processes: (1) Classifying the intelligence level of SIPs through expert interviews; (2) Using the literature analysis method to identify various dimensions of the intelligence level; (3) Using literature analysis and expert interviews to determine the evaluation indicators (4) Weighting indicators based on correlation and induced ordered weighted average (IOWA) operator; (5) Using grey clustering analysis to calculate the overall intelligence performance of SIPs and each dimension. Finally, the developed model was verified by Z SIP. The analysis results show that the developed model can measure both overall and dimensional performance of SIPs, and demonstrated that enterprise information services, public information services, SIP security, and energy consumption monitoring platform construction make the greatest contributions to the improvement of the intelligence level. Our research results will help to improve the intelligence level of SIPs, and lay the foundation for the determination of the operating costs of SIPs and the formulation of national standards related to SIPs in the future. [ABSTRACT FROM AUTHOR]

The intelligent development of smart industrial parks (SIPs) can not only promote the development of smart cities, but also promote the development of intelligent large-scale buildings. China is strengthening the construction of SIPs; however, the development of SIPs is limited. Due to different understandings of SIPs, the intelligence level of each SIP varies greatly. It is necessary to develop a SIP intelligence level assessment model to check these limitations. Most of the existing evaluations focus on the qualitative evaluation of the overall intelligence level of SIPs, ignoring the influence of each individual dimension. Therefore, this study used quantitative methods to measure the intelligence level of SIPs from the overall and dimensional levels. The evaluation method included five processes: (1) Classifying the intelligence level of SIPs through expert interviews; (2) Using the literature analysis method to identify various dimensions of the intelligence level; (3) Using literature analysis and expert interviews to determine the evaluation indicators (4) Weighting indicators based on correlation and induced ordered weighted average (IOWA) operator; (5) Using grey clustering analysis to calculate the overall intelligence performance of SIPs and each dimension. Finally, the developed model was verified by Z SIP. The analysis results show that the developed model can measure both overall and dimensional performance of SIPs, and demonstrated that enterprise information services, public information services, SIP security, and energy consumption monitoring platform construction make the greatest contributions to the improvement of the intelligence level. Our research results will help to improve the intelligence level of SIPs, and lay the foundation for the determination of the operating costs of SIPs and the formulation of national standards related to SIPs in the future.

Currently, there are two main problems with the evaluation of college English teaching quality: the lack of a complete evaluation system, and the limited quantification of evaluation indices. To solve the problems, this paper sums up the evaluation contents of college English teaching quality, and identifies the factors affecting the teaching quality of college English. On this basis, an improved evaluation system was established for the assessment of college English teaching quality, which is theoretically innovative. Next, grey clustering analysis and entropy weight method were combined into a robust evaluation model for college English teaching quality. This research provides a new and applicable solution to quantification of college English teaching quality. [ABSTRACT FROM AUTHOR]

In order to solve the problem of the lack of reliability data and the uncertain factors in the product development stage,a reliability allocation model based on grey system theory was proposed. Considering 6 effecting factors such as the importance,complexity, technology development level, manufacturing level, working time and environmental conditions,combining with the expert experience and known reliability data,the relative failure relationship among fuel cell vehicle subsystems was elevated using improved method of solving index weight based on grey correlation. The reliability of each subsystem was allocated according to the comprehensive grey evaluation value. Compared with the actual failure data,the validity of this model was verified.

Today's leading businesses have understood the role of 'social' in their everyday activity. Online social networks (OSN) and social media have melt and become an essential part of every firm's concern. Brand advocates are the new leading triggers for company's success in online social networks and are responsible for the long-term engagement between a firm and its customers. But what can it be said about this impressive crowd of customers that are gravitating around a certain brand advocacy or a certain community? Are they as responsive to a certain message as one might think? Are they really impressed by the advertising campaigns? Are they equally reacting to a certain comment or news? How they process the everyday grey knowledge that is circulating in OSN? In fact, how impressionable they are and which are the best ways a company can get to them? To give an answer to these questions, the present paper uses grey systems theory for spreading the customer's crowd into groups based on how impressionable they are by commercials, ads, videos and comments in OSN. [ABSTRACT FROM AUTHOR]

Investments are accompanied by risks. How investors choose the right investment tools to assist in the selection of investment targets is a topic worth exploring. Therefore, this study aimed to develop an investment decision-making process to deal with this issue. Firstly, we proposed a globalized modified grey relational analysis to select the representative indicators including the financial indicators and risk measurement indicators. Then we combined financial and risk evaluation indicators, and divided companies into low, moderate and high-risk groups through the grey clustering analysis. Finally, Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) combined with the grey entropy weighting method was applied to business performance evaluation and sorting of each grouping. In order to verify this study, a combination of 21 financial ratios and four risk indicators was utilized in order to verify the evaluation and decision-making process in the operating performance of 62 listed opto-electronics companies in Taiwan. The results of ranking the operating performance for each group can be made available to company managers as a reference in order to enhance competitiveness and business performance. The results can also be used as the basis for decision-making to aid investors who are facing many investment portfolios.

Teaching quality evaluation of physical education usually involves multiple influence factors with grey and uncertain information. This brings about limitations to effective evaluation of teaching quality of physical education in colleges and universities. Thus, this paper draws merits from previous research and proposes a teaching quality evaluation system and model of physical education in colleges and universities. First, based on real situations, grey categories of evaluation state for physical education teaching quality are established. The definite weighted functions of grey category of evaluation state are confirmed. Specific steps of the teaching quality evaluation model based on grey clustering analysis are accounted for. Finally, a case study is introduced to verify the model. This model enlightens a new way to evaluate teaching quality of physical education in colleges and universities. [ABSTRACT FROM AUTHOR]

Investments are accompanied by risks. How investors choose the right investment tools to assist in the selection of investment targets is a topic worth exploring. Therefore, this study aimed to develop an investment decision-making process to deal with this issue. Firstly, we proposed a globalized modified grey relational analysis to select the representative indicators including the financial indicators and risk measurement indicators. Then we combined financial and risk evaluation indicators, and divided companies into low, moderate and high-risk groups through the grey clustering analysis. Finally, Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) combined with the grey entropy weighting method was applied to business performance evaluation and sorting of each grouping. In order to verify this study, a combination of 21 financial ratios and four risk indicators was utilized in order to verify the evaluation and decision-making process in the operating performance of 62 listed opto-electronics companies in Taiwan. The results of ranking the operating performance for each group can be made available to company managers as a reference in order to enhance competitiveness and business performance. The results can also be used as the basis for decision-making to aid investors who are facing many investment portfolios. [ABSTRACT FROM PUBLISHER]

Abstract: Deng proposed grey clustering analysis (GCA) in 1987. Later, Jin presented a new method in 1993, called grey relational clustering (GRC) method that combined grey relational analysis with clustering. However, the GRC method cannot use a tree diagram to make appropriate classification decisions without re-computation. This study thus attempts to combine GRC and hierarchical clustering analysis. Given the existence of an excess of medical resources in the Taipei area, this study attempts to understand the degree of concentration of medical resources in this area. Specifically, this study applies a geographical information system (GIS) to present the geographical distribution of hospitals in Taipei. Additionally, a new-type of cluster analysis, known as hierarchical grey relation clustering analysis, is used to analyze the distribution of hospitals and understand how they compete with one another. The analytical results demonstrate that hierarchical grey relation clustering analysis is a suitable method of analyzing geographical position. Tree diagrams can help policymakers make appropriate classification decisions without re-computation. The study results can inform hospitals of their competitors and help them to develop appropriate responses. Additionally, the analytical results can also provide a reference to government or hospital policymakers to help them position hospitals in areas, thus achieving a better distribution of medical resources in Taipei. [Copyright &y& Elsevier]

Abstract: An intelligent decision-making method has been put forward to deal with overseas project loans decision-making, which is based on grey clustering analysis method. The grey clustering analysis is an algorithm based on the risk classification causes risk index system which clusters risk of harm degree into grey clustering risk index system, and realizes the decision overseas project loans to measure the risk accurately, and also can measure the results as a sample data set clustering analysis to get to the loan plan for clustering center decision model to complete the project implementation plan outside loans. The effectiveness of the method through the contrast experiment has been validated. [Copyright &y& Elsevier]

A method is proposed for dissolved gases forecast and fault diagnosis in oil-immersed transformers using grey prediction-clustering analysis. Incipient faults can produce hydrocarbon molecules and carbon oxides due to the thermal decomposition of mineral oil, cellulose and other solid insulation. Dissolved gas analysis is employed to detect and monitor abnormal conditions in oil-immersed power transformers. However, the procedure takes a long time to decompose overall key gases and monitor conditions. The grey prediction GM(1, 2) model uses the variant information of hydrogen to forecast the further trends of both combustible and non-combustible gases. Grey clustering analysis is applied to diagnose internal faults including thermal faults, electrical faults and faults involving cellulose degradation. Numerical tests with field gas records were conducted to show the effectiveness of the proposed model, and are easy to implement with the help of portable devices. [ABSTRACT FROM AUTHOR]

The forest ecological security of the Yangtze River Economic Belt has an important influence on improving the regional environment and promoting the sustainable development of the social economy. Therefore, the aim of this paper is to provide countermeasures and suggestions for improving the level of regional ecological security by quantitatively analyzing the forest ecological security status of the Yangtze River Economic Belt and the tributaries of the Yangtze River. Using three main aspects, i.e., resources, socio-economic pressure and maintenance response, the study established 26 indicators that affect the forest ecological security of 11 provinces (cities) in the Yangtze River Economic Belt. The index weights were determined by principal component analysis, and the forest ecological security levels of 11 provinces (cities) in the Yangtze River Economic Belt were classified and evaluated by the grey clustering method. The results show the following: (1) the principal component analysis determined the weight of the three aspect indicators. The order is as follows: resource index > socio-economic pressure index > maintenance response index. This means that the basic environmental condition which the forest growth depends on and quality and quantity of forest is most important, and the maintenance activities performed by human beings in forest resources need to be strengthened. (2) The level of the forest ecological security in all the provinces (cities) of the Yangtze River Economic Belt is relatively good, with an upward trend. The level of forest ecological security in each province (city) decreases from the upper reaches of the Yangtze River basin to the lower reaches, and the level of forest ecological security in the central cities is lower. (3) The resource index, socio-economic pressure index and maintenance response index of all the provinces and cities showed an upward trend in these four years. The provinces with a significantly higher forest resource index include Yunnan and Guizhou. Shanghai, Chongqing, Sichuan, Hunan and Jiangxi were the provinces with significantly higher socio-economic pressure values; Yunnan province, Shanghai, Jiangxi Province and Hubei province were the provinces with higher forest maintenance response values. [ABSTRACT FROM AUTHOR]

Most concrete dams have seepage problems to some degree, so it is a common strategy to maintain ongoing monitoring and take timely repair measures. In order to grasp the real operation state of dam seepage, it is vital to analyze the measured data of each monitoring indicator and establish an appropriate prediction equation. However, dam seepage states under the load and environmental influences are very complicated, involving various monitoring indicators and multiple monitoring points of each indicator. For the purpose of maintaining the temporal continuity and spatial correlation of monitoring objects, this paper used a multi-indicator grey clustering analysis model to explore the grey correlation among various indicators, and realized a comprehensive evaluation of a dam seepage state by computation of the clustering coefficient. The case study shows that the proposed method can be successfully applied to the health monitoring of concrete dam seepage. [ABSTRACT FROM AUTHOR]