Grey Incidence Analysis Model Research Articles

A superimposed current based busbar protection scheme using slope degree of grey incidence analysis model

Superimposed current components contain effective information, which can be employed to enhance the dependability and security of busbar protection relays. This study aims to investigate the use of the slope degree of grey incidence analysis model to design a methodology for busbar protection. A grey-based busbar protection criterion has been established to inspect the similarities of the superimposed currents measured by nearby CTs inside busbar protection zone. It is concluded that fault is internal if all of the superimposed currents are similar, otherwise, fault is external. It is shown that in all of the simulated cases, the authors’ methodology can make reliable discrimination between internal and external faults. Moreover, the results demonstrated that the protection indexes of the proposed scheme including security, dependability, sensitivity, and selectivity, are satisfactory for different conditions including fault type, fault resistance (to 500 Ω), fault inception angle, simultaneous faults, evolving faults, faults during transformer energization, CT saturation and normal operating switchings and white noise. Besides, the improvements noted in our algorithm are achieved with a low computational burden and sampling rate. Also, the scheme can be implemented in digital relays. It means that the existing busbar protection scheme can be replaced by the proposed scheme.

Evaluating the performance of chemical transport models for PM2.5 source apportionment: An integrated application of spectral analysis and grey incidence analysis.

Evaluating the performance of source apportionment (SA) models is difficult due to the non-observable nature of source contribution in reality. Here we propose a new approach to assess the performance of Chemical Transport Models (CTMs) for SA based on wavelet time-frequency spectral analysis and Grey Incidence Analysis (GIA). For each source category, certain species that better reflect the periodic characteristics of the emission sources were selected as the chemical tracers. The consistency of the time series between the simulated source contributions and the observed source-specific chemical tracers was then examined using a GIA model based on the perspective of similarity, and characterized by the GIA scores. By applying this method to six typical pollution episodes, we evaluated the performance of the Comprehensive Air Quality Model with Extensions-Particle Source Apportionment Technology (CAMx-PSAT) model for PM2.5 SA from different temporal and spatial scales. The source- and episode-dependent optimal average time and main source regions were obtained. This approach is robust for facilitating a relatively meticulous evaluation of the performance of CTMs for PM2.5 SA, and provides additional insight for decision-making for heavy pollution emergencies.

A Grey Incidence Based Group Decision-Making Approach and Its Application

We define the group measure matrix of the alternative scheme and the ideal scheme based on the relevant factor sequence and the system characteristic behavior sequence. Furthermore, the information distances of decision makers and decision criteria are defined, respectively. According to the information distance, we obtain each scheme’s grey matrix incidence degree for the scheme ranking. Finally, we use an example to verify the rationality of the model and compare it with other classic methods, such as TOPSIS, VIKOR, MULTI-MOORA. Compared with previous grey incidence analysis model, the proposed model can make full use of information of the decision-maker dimension and the criteria dimension. The proposed model can avoid high-dimensional information loss. The results show that the proposed method has superiority in measuring decision-maker information and decision-making standard information.

Analysis of Agricultural Eco-Efficiency and Influencing Factors in Henan Province

In order to improve the agricultural eco-efficiency and promote the sustainable development of agriculture in Henan Province, China, based on the footprint theory, the super-efficiency SBM model is used to scientifically calculate and analyze the agricultural eco-efficiency in Henan Province. On this basis, the influencing factors of agricultural eco-efficiency in Henan Province are quantitatively analyzed by using the grey incidence analysis model. The results show that unilaterally considering one of grey water footprints and carbon footprints will overestimate or underestimate the agricultural eco-efficiency of Henan Province in different degrees in different time periods, and the agricultural eco-efficiency obtained by comprehensively considering grey water footprint and carbon footprint (GWCAEE) is more in line with the reality of agricultural development in Henan Province. In 2000-2004, GWCAEE in Henan Province was better. During 2005-2014, GWCAEE in Henan Province showed a fluctuating decline and continued to be in an inefficient state. From 2015 to 2019, GWCAEE of Henan Province gradually increased, and it became effective in 2019. In recent years, GWCAEE has developed well. Through the grey incidence analysis between 12 influencing factors including endogenous factors and exogenous factors and GWCAEE, it is found that the six leading factors of GWCAEE in Henan Province are agricultural structure, financial input for agriculture, number of agricultural employees, crop sown area, consumption of chemical pesticide, consumption of agricultural diesel oil. According to the above research conclusions, suggestions for improving agricultural eco-efficiency in Henan Province are put forward.

Efficiency Analysis of Scientific and Technological Innovation in Grain Production Based on Improved Grey Incidence Analysis

Analyzing and evaluating the efficiency of scientific and technological innovation in grain production is conducive to the rational allocation of resources, promoting the development of scientific and technological innovation in grain production and providing guarantee for grain security. By refining the elements of grain production and scientific and technological innovation, an evaluation system of scientific and technological innovation in grain production is constructed. Firstly, combining linear programming together with the traditional grey synthetic incidence analysis model, a incidence analysis of the scientific and technological innovation indicators of grain production is carried out, and the key and secondary indexes affecting grain outputs are screened by an improved grey incidence analysis model. Secondly, based on DEA-Malmquist index model and taking the grain production process as the research object, the scientific and technological achievement transformation indicators are divided into pre-production, in-production and post-production indicators. The key indicators and secondary indicators of scientific and technological innovation of grain production in various cities of Henan Province from 2010 to 2019 are used to analyze the efficiency of scientific and technological innovation in each stage of grain production. The results show that: (1) The type of basic ability of scientific and technological innovation indicators and the transformation ability of scientific and technological innovation achievements are the major indicators influencing grain outputs, and the investment of basic resources of scientific and technological innovation and the transformation of scientific and technological innovation achievements are the most important to improve grain outputs. (2) In addition, the study reveals that the secondary indicators of the technological innovation efficiency of grain production based on the DEA-Malmquist index model are more efficient than the key indicators in the pre-production, in-production and post-production stages. And there are gaps in the scientific and technological innovation performance of grain production among cities in Henan Province, and the index of technological progress is the leading factor for the gap.

Does temperature matter for COVID-19 transmissibility? Evidence across Pakistani provinces.

The outbreak of novel coronavirus (COVID-19) has become a global concern that is deteriorating environmental quality and damaging human health. Though some researchers have investigated the linkage between temperature and COVID-19 transmissibility across different geographical locations and over time, yet these studies are scarce. This study aims to bridge this gap using daily temperature and COVID-19 cases (transmissibility) by employing grey incidence analysis (GIA) models (i.e., Deng’s grey incidence analysis (DGIA), the absolute degree GIA (ADGIA), the second synthetic degree GIA (SSDGIA), the conservative (maximin) model) and correlation analysis. Data on temperature are accessed from the NASA database, while the data on COVID-19 cases are collected from the official website of the government of Pakistan. Empirical results reveal the existence of linkages between temperature and COVID-19 in all Pakistani provinces. These linkages vary from a relatively stronger to a relatively weaker linkage. Based on calculated weights, the strength of linkages is ranked across provinces as follows: Gilgit Baltistan (0.715301) > Baluchistan (0.675091) > Khyber Pakhtunkhwa (0.619893) > Punjab (0.619286) > Sindh (0.601736). The disparity in the strength of linkage among provinces is explained by the discrepancy in the intensity of temperature. Besides, the diagrammatic correlation analysis shows that temperature is inversely linked to COVID-19 cases (per million persons) over time, implying that low temperatures are associated with high COVID-19 transmissibility and vice versa. This study is among the first of its kind to consider the linkages between temperature and COVID-19 transmissibility for a tropical climate country (Pakistan) using the advanced GIA models. Research findings provide an up-to-date glimpse of the outbreak and emphasize the need to raise public awareness about the devastating impacts of the COVID-19. The educational syllabus should provide information on the causes, signs, and precautions of the pandemic. Additionally, individuals should practice handwashing, social distancing, personal hygiene, mask-wearing, and the use of hand sanitizers to ensure a secure and supportive atmosphere for preventing and controlling the current pandemic.

Evaluating Unemployment through Grey Incidence Analysis Model: A Study of One Hundred Thirteen Selected Countries

The purpose of the study is to gauge the unemployment level of selected one hundred and thirteen countries. The design of the study includes a survey of the literature, extraction of relevant data and analysis. The study follows a quantitative paradigm of research that uses secondary data set taken from the website of World Development Indicators (WDI). The analysis encompasses selected countries based on the availability of data. The data has been analyzed using Grey Incidence Analysis Model, commonly known as GRA. For interpretation of the results, the methodology has been augmented with the scheme of ensigns (i.e. classification of countries into Extremely Low, Very Low, Low, Moderate, High, Very High, Extremely High) of the level of unemployment. Results show that J&APR have an extremely low level of unemployment and member countries of SADC have an extremely high level of unemployment. Pakistan fall under the ensign of very low, therefore have a low level of unemployment. It is valuable to study equally useful for governments, academia and the international community. This study provides critical new information on the phenomenon.

Towards environmental sustainability: Exploring the nexus among ISO 14001, governance indicators and green economy in Pakistan

Abstract The green growth paradigm has gained much attention in the last decade. Green growth not only protects the environment and human beings but also serves as a substitute for scarce natural assets. Governance institutions develop laws and policies for all industries in a country and are directly responsible for natural resource exploration and environmental protection or destruction. Pakistan is the fifth most vulnerable country to environmental hazards in the world. To address this issue, this study is the first to analyze the relations among governance indicators, ISO 14001 and green growth in Pakistan by using time-series data from 2000 to 2017. The study utilized advanced mathematical Grey Relational Analysis (GRA) models, namely, absolute grey relational grade (GRG), Deng's GRG, and Second Synthetic Degree of Grey Incidence Analysis (SSGIG) models, to capture the relations among the studied variables. The main results revealed that ISO 14001, with the highest GRA values of 0.8-0.9, proved to be effective in channeling green growth. Among all governance indicators related to green growth, the rule of law with the highest maximin criterion value of 0.644 was found to play a key role for Pakistan. The study findings provide insights into how good governance can contribute to accomplishing the objectives of environmental sustainability. They can also help legislators and organizations understand the importance of ISO 14001 certification to promote sustainable practices across sectors in Pakistan.

Composite Appraisal of Women Development in Selected Thirty-six Countries with Special Focus on Pakistan: Applying Grey Incidence Analysis Model

Aim of the study is to appraise women development in selected thirty-six countries with special reference to Pakistan. The design of the study comprises of survey of literature, data elicitation and analysis. The study uses grey incidence analysis model (usually known as Grey Relational Analysis or simply GRA). The model has been applied on the secondary data extracted from the website of World Development Indicators (WDI). The countries included in the analysis have been selected on the basis of availability of data. From the result of GRA it can be learnt that thirty-six countries of the world are classified into seven different categories. There are five countries (namely Estonia, Hungary, Slovak Republic, Thailand and Ecuador) categorized as countries having exceptionally high women development, whereas, five countries under each next ensign (very high, high, moderate, low and very low). There are six countries (namely Tanzania, Madagascar, Cote d'Ivoire, Pakistan, Nigeria and Afghanistan) categorized under the ensign of exceptionally low. Pakistan fall under the ensign of exceptionally low. This study is designed on an original country level data extracted from very reliable source and the results of the study are useful for regulators, researchers, NGOs and other stakeholders of the phenomenon by way of providing deeper and new information.

General grey number decision-making model and its application based on intuitionistic grey number set

PurposeThe purpose of this paper is to study the grey decision model and distance measuring method of general grey number.Design/methodology/approachFirst, intuitionistic grey number (IGN) set and an IGN are defined by grey number probability function. Second, each interval grey number in general grey number is represented by an IGN and converts the general grey number into an IGN set. Final, the operation of two general grey numbers is defined as the operation between IGN sets, and the distance measure of the general grey number is given.FindingsUp to now, the method of measuring the distance and the grey decision model of general grey number is established. Thus, the difficult problem for set up decision mode of general grey number has been solved to a certain degree.Research limitations/implicationsThe method exposed in this paper can be used to integrate information form a different source. The method that a general grey number converted to a set of IGNs could be extended to the case of grey incidence analysis models, grey prediction models and grey clustering evaluation models, which includes general grey numbers, etc.Originality/valueThe concepts of IGN and IGN set are proposed for the first time in this paper; The operation of two general grey numbers can be defined as the operation between IGN sets. On this basis, the algorithm of IGN, the integration operator of IGN and the distance measure between IGN sets are given.

Sensitivity Analysis of Factors Affecting Stability of Cut and Fill Multistage Slope Based on Improved Grey Incidence Model

There are many factors affecting the stability of cut and fill multistage slopes, and these factors exert different degrees of influence on slope stability. The grey incidence analysis method can be used to evaluate the sensitivity of these factors. To overcome the shortcomings of the grey incidence analysis model used in previous sensitivity analysis studies on the factors influencing slope stability, this study improved the dimensionless processing method and resolution coefficient value. Considering that the importance of each influencing factor is different, the vector resemblance degree theory was applied to determine the weight of each influencing factor. Finally, based on an actual cut and fill multistage slope, the sensitivity of the factors affecting stability was analyzed according to the improved grey incidence analysis theory. The results revealed that the unloading platform width, cohesion force, and internal friction angle are most sensitive to the stability of the cut and fill multistage slope. The step height, slope width, and slope height are slightly sensitive, while the soil unit weight, seismic peak acceleration, and slope ratio are the least sensitive.

Driving Mechanism of the Coordinated Development of Regional Economy-Society-Environment System Based on Grey Incidence Analysis Model<br/>—A Case Study of Wanjiang Urban Belt

Using grey incidence analysis method, this paper analyzed the impact of various factors on the coordinated development of economy-society-environment system of Wanjiang urban belt to explore the mechanism of the coordinated development of regional economy-society-environment system. From 2011 to 2018, in the coordinated development of economic, social and environmental systems under the overall level of Wanjiang urban belt, the degree of influence of the development of each subsystem on the coordinated development is ranked: environmental subsystem economic subsystem social subsystem. In the environmental subsystem, environmental state = environmental pressure environmental response, and surface water quality, per capita industrial solid waste production, green coverage of constructed areas are three most influential social indicators. In the economic subsystem, economic structure developing quality economic benefits, proportion of foreign direct investment in GDP, the proportion of R & D expenditure in GDP, the proportion of tertiary industry in GDP are three most influential economic indicators. In the social subsystem, public service living standards quality of life, and urbanization rate of permanent population, per capita road mileage, and the number of hospital beds per 10,000 people are three most influential social indicators.

A novel grey object matrix incidence clustering model for panel data and its application

In order to fully excavate the information contained in the multi-index panel data, one take decision objects as the research object, and the development state matrix and the development speed matrix of the decision objects are defined by considering the cross-section information and time information of the decision objects, and then the distances among the objects over the indexes are given. Based on grey incidence analysis, the absolute difference and relative difference between the measure value matrices are used to characterize and measure the close degree of the development state matrix and the development level matrix of the decision objects, so that the grey object matrix absolute incidence analysis model is established, and then according to the grey incidence degree between the objects, the objects can be clustered based on hierarchical clustering algorithm. Finally, a clustering problem of regional patent research and development (R&D) efficiency is used to verify the validity and rationality of the proposed model.

Operational capability evaluation based on improved generalized grey incidence analysis model

To solve the problem of operational capability evaluation of weapon equipment system-of-systems (WESoS), a capability-based method is proposed based on an improved generalized grey incidence analysis (GGIA) model. A hierarchy description framework is proposed, which establishes a mapping relationship between weapons and operational capabilities. Four types of capability requirement functions are proposed to assess the performance of weapons on tactical indicators. The deficiencies of the traditional GGIA model are analyzed, and the improvement is proposed to calculate the satisfaction degree of weapon equipment to a certain operational capability. Then, regardless of other subjective factors, the contribution degree of a certain operational capability to WESoS is determined combined with the maximum entropy model and genetic algorithm. Finally, the feasibility and effectiveness of the proposed algorithm are verified by experimental comparison.

Bidirectional Absolute GRA/GIA Model for Uncertain Systems: Application in Project Management

This paper extends the existing absolute grey relational analysis (Absolute GRA) model, also called the absolute degree grey incidence analysis (ADGIA) model. By working on the limitations of the existing Absolute GRA model, the proposed model, named Bidirectional Absolute GRA (BAGRA) model, is better equipped to handle uncertain systems being represented by uncertain data. It is suitable for simultaneous handling of both linear and nonlinear arrays of data with both consistent and inconsistent directions of motion. The model introduces a bidirectional grey relational degree that is a composite measure of both direction and strength of the relationship. The study also introduced two scales to test the appropriateness of collected data to measure the confidence level on the information extracted from that data. In the end, after the pilot testing, the model is being applied on an R&D project management case from a real world. The work is important both theoretically and practically, especially for the data analysts concerned with the uncertain relationships between different data arrays, in general, and for the grey systems analysts, in particular.

Decision-making approach by employing grey incidence analysis and group negotiation

For the problems of the consistency ranking of the group decision-making scheme, from the view of group negotiation and system coordination, the grey incidence analysis and Nash bargaining model are used to establish a consistency group decision-making method. First, the concepts of the consensus partial decision-making program and the consensus overall ideal decision-making program are defined, and then a multi-object optimization model is constructed based on the satisfaction maximization of group negotiation and deviation minimization of system coordination to determine the consensus partial decision-making program and the consensus overall ideal decision-making program. Moreover, the grey incidence analysis is exploited to measure the close degrees between them. Finally, a real case of the online product evaluation verifies the validity and rationality of the proposed model.

An improved grey group decision-making approach

In complex group decision-making, decision makers and decision attributes are the core of the relevant activities. Targeting the problem of scheme ranking and behavioural characteristics that exist in group decision-making, from the perspective of group negotiation and decision-making system coordination, by exploiting the grey target and grey relation analysis, this paper establishes a novel grey group decision-making approach. We define a group measure matrix of scheme, consensus ideal scheme, and decision-making resource coefficient. Then, by borrowing Nash’s bargaining idea, and maximizing group negotiation satisfaction and minimizing system coordination deviation, we construct a two-step optimization model to solve for the group consensus ideal scheme and its measure value matrix. In addition, we take decision-making schemes as research objects; and from the two dimensions of decision maker and attribute, we characterize and measure the closeness degree of decision maker information and attribute information by using the distance between the group measure matrices of scheme and consensus ideal scheme, so that we are able to construct a novel grey scheme matrix similar incidence analysis model. Lastly, we take the group decision-making problem of selecting the location of a garbage disposal station as a case analysis, and explore the economic significance and theoretical value of the model.

On modeling mechanisms and applicable ranges of grey incidence analysis models

PurposeThe purpose of this paper is to study the modelling mechanisms of several grey incidence analysis models with great influence, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model; then analyse the problems to be solved in grey incidence analysis models; and clarify the applicable ranges of commonly used grey incidence models.Design/methodology/approachThe paper comes to conclusions by means of comparable analysis. The authors compare several commonly used grey incidence analysis models, including Deng’s grey incidence model, absolute degree of grey incidence model, slope degree of incidence model, similitude degree of incidence model and closeness degree of incidence model and give several examples to clarify the reasons why quantitative analysis results of different models are not exactly the same.FindingsAs the intension of each kind of incidence model is clear and the extension is relatively obscure, grey incidence orders calculated by different incidence models are often different. When making actual decisions, incompatible results may appear. According to different characteristics of extraction, grey incidence analysis models can be divided into three types: incidence model based on closeness perspective, incidence model based on similarity perspective and incidence model based on comprehensive perspective.Practical implicationsThe conclusions obtained in this paper can help people avoid some defects in the process of actual selection and choose the better incidence analysis model.Originality/valueThe conclusions can be used as a reference and basis for the selection of grey incidence analysis models, it can help to overcome the defects and shortcomings of models caused by themselves and screen out more excellent analytical models.

Key factors selection approach for SMCDA problem based on GIA model with rate of change

PurposeThe purpose of this paper is to construct a key factors selection approach for a class of small-sample multi-factor cross-sectional data analysis (SMCDA) problem, which is very common in productive practice and scientific research, such as coal-bed methane (CBM) content analysis, civil aircraft cost analysis, etc. Key factors selection is an important basic work for SMCDA problem; the proposed method is constructed to improve the accuracy and explanatory of the selected key factors.Design/methodology/approachUsing grey system theory to solve SMCDA problem is more reasonable under few data and poor information. Therefore, this paper constructs a grey incidence analysis (GIA) model with rate of change to select the key factors of an SMCDA problem. The basic idea of the proposed method is to simulate time series by randomly sorting the selected samples, and to calculate the degree of grey incidence with rate of change by loop iterative algorithm, then to construct the degree matrix of grey incidence with rate of change, and finally by which, to utilise quantitative and qualitative analysis methods to select the key factors.FindingsThe experimental analysis of application cases demonstrates that the key factors of system’s characteristic can be successfully screened out by the proposed method, the results are consistent with actual conditions, and they have a clearer meaning and a better interpretability.Practical implicationsThe method proposed in this paper could be utilised to select key factors for such a class of SMCDA problem, which has fewer observation samples (small-sample), which is influenced by a number of factors (multi-factor) and whose observation samples are placed randomly rather than by time (cross-sectional data). Taking the key influence factors of CBM content and the key driving factors of the vulnerability of agricultural drought in Henan as examples, the results proved the feasibility and superiority of this proposed method.Originality/valueMost of the existing GIA models mainly focus on these classes of issues with time series data or panel data. However, few GIA models take SMCDA problem as the research object. In this paper, the authors develop the GIA model with rate of change according to the characteristics of SMCDA problem, and present some properties and application suggestions of the proposed method.

Research on factors influencing consumers’ loyalty towards geographical indication products based on grey incidence analysis

PurposeLoyalty of customers is an essential factor influencing the development of geographical indication products industry. The purpose of this paper is to construct a model to detect factors influencing customers’ loyalty on geographical indication products. With analysing four teas, i.e., Lu’an Gua Pian, Huoshan Huangya, Huangshan tribute chrysanthemum and Yuexi Cuilan, this paper measures the factors strengthening consumers’ loyalty and examines how much impact these factors have.Design/methodology/approachThis paper is characterised as an exploratory research using the grey incidence analysis model and data are obtained by questionnaire survey.FindingsIn general, result of the analysis indicates that customer’s attitude towards its producing areas, perceived quality and cognition of the protection of geographical indications are the important factors that influence their loyalty towards geographical indication products. Detailed rank of their power that goes from highest to lowest is: customer’s attitude towards its producing areas, perceived quality and cognition of the protection of geographical indications. It also shows that the method of grey incidence analysis is adaptable to evaluate factors affecting consumers’ loyalty, which can make the result more persuasive and objective.Originality/valueThe authors construct a model from three aspects: customer’s attitude towards the producing areas of geographical indication products, the perceived quality and cognition of the protection of geographical indications. On the basis of this model, the authors analyse the factors which influence customer’s loyalty with grey incidence analysis.