Grey Incidence Analysis Method Research Articles

Study on H-shaped fracture propagation and optimization in shallow dull-type coal seams in the Hancheng block, China

The initiation and propagation of hydraulic fractures dominate the fracture morphology and conductivity, thereby determining the fracturing stimulation effect. This work took the shallow dull-type coal seam in the Hancheng block as the research object, and focused on the propagation and optimization of the H-shaped fracture. By using a combination of mechanical theoretical analysis, laboratory experiment, numerical simulation, field test, and optimization evaluation, an integrated study on the formation conditions, morphology evolution, propagation laws, main controlling factors, and optimal design of H-shaped fractures was conducted. The mechanical criterion for identifying H-shaped fracture propagation was derived through the analysis of the stress fields on the fracture surface. A 3D numerical model of H-shaped fractures was established with cohesive element method, and the propagation law and influencing factors of H-shaped fractures were investigated. Sensitivity analysis of the influencing factors on the H-shaped fractures was performed with grey incidence analysis method. The optimization of the H-shaped fracture parameters was performed by fracture propagation numerical simulation. The results show that H-shaped fractures dominated by horizontal fractures are generally formed in shallow dull-type coal seams. H-shaped fractures can improve the CBM development effect by parameter optimization of indirect fracturing technology. The judging criterion for H-shaped fracture formation is that the tensile strength of the upper and lower weakly cemented horizontal interfaces is less than that of the coal seam and the vertical principal stress is lower than the minimal horizontal principal stress. The incidence degree of fracturing fluid injection rate, viscosity, perforation location, minimum horizontal stress difference, and coal seam permeability on the H-shaped fracture propagation decreases in turn. The engineering factors (fracturing fluid injection rate and viscosity and perforation location) are the major impact factors. With the increase in coal seam permeability, the horizontal fracture develops from stubby-type to slender-type. The minimum horizontal principal stress difference mainly affects the horizontal fracture. As the fracturing fluid viscosity increases, the horizontal fracture length increases first and then decreases. The fracturing fluid injection rate has a great impact on the height-length profile of horizontal fractures. The optimal injection rate seems to be 6.5–7 m3/min, the optimal fracturing fluid viscosity is between 10 mPa·s and 15 mPa·s, and the optimal perforation location is selected near the formation interface. These research results could provide a reference for the design and optimization of efficient fracturing of coalbed methane reservoirs.

A CM&CP framework with a GIACC method and an ensemble model for remaining useful life prediction

Data-driven methods based on health indicators (HIs) have been proven effective for remaining useful life (RUL) prediction. Significant differences may exist among HI degradation sequences due to various equipment failure behaviors. In order to solve this problem, the first clustering then modeling and first classifying then predicting (CM&CP) framework for RUL prediction is often used. Differently, for the processes of clustering and classifying in the framework, the grey incidence analysis (GIA) method is first proposed to measure the similarity level of two sequences; and the GIA-based clustering and classifying (GIACC) method is suggested. The ensemble model with multiple appropriate machine learning models as its base learners for RUL prediction is trained for each cluster, aiming to achieve good prediction accuracy and high computational efficiency. Since aero engines have various failure modes, the related datasets are used to verify the effectiveness of the proposed method. The case study shows that the CM&CP framework with the GIACC method and the ensemble model can achieve good performance in both prediction accuracy and computational time and provide stable support for equipment health management, especially under multiple failure modes.

Industry 4.0 and Higher Education: An Evaluation of Barriers Affecting Master’s in Business Administration Enrolments Using a Grey Incidence Analysis

Higher education confers numerous benefits both to the individual and to society, including higher earnings, lower rates of unemployment and government dependency, an increased tax base, and greater civic engagement. Access to higher education remains a challenge for many families. The emergence of Industry 4.0 will not only affect technological changes but also people in the labour market. As such, higher education institutions with academic responsibilities of formally training students to better adapt to such changes are not left out. Since the introduction of the Master of Business Administration (MBA) in the United States of America in 1908 and over one hundred years of history, this prestigious programme has suffered a rapid decline in enrolments worldwide. Thus, it has gradually lost its value under the current industrial revolution. This paper evaluates and prioritizes barriers affecting the decline in international MBA enrolments. Understanding the key barriers to MBA enrolments regarding the dynamics will contribute to the successful implementation of those barriers. With scarce information, this study innovatively applies the grey incidence analysis (GIA) method to prioritizing the identified barriers. When applied, this method provided a robust prediction of results. For international MBA enrolments decline, the barrier “employment difficulties” (H3) should receive much attention from policymakers because it scored the highest among the barriers ranked. Further, other important barriers that should be considered are “lack of entrepreneurship skills” (H11), “high cost” (H10), “longer payback duration” (H1), “10 yr. ROI” (H9), and “lack of data analytic skills” (H7). Therefore, during the formulation and implementation of policy to address these prioritized barriers, scarce resources must be committed to them. This paper also contributes to the literature a first-hand, formal study on the prioritization of barriers to international MBA enrolments.

Analysis and Prediction of Wear Performance of Different Topography Surface.

Surface roughness parameters are an important factor affecting surface wear resistance, but the relevance between the wear resistance and the surface roughness parameters has not been well studied. This paper based on the finite element simulation technology, through the grey incidence analysis (GIA) method to quantitatively study the relevance between the wear amount of per unit sliding distance (ΔVs) and the surface texture roughness parameters under dry friction conditions of the different surface topography. A zeroth order six-variables grey model, GM(0,6), for prediction the wear characteristic parameter ΔVs was established, and the experiment results verified that the prediction model was accurate and reasonable.

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.

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.

Key indices of the remanufacturing industry in China using a combined method of grey incidence analysis and grey clustering

Remanufacturing is a critical tool for solving resource depletion and environmental deterioration by reducing raw material and embedded energy consumption. The Chinese government, like many other countries, has been keenly interested in remanufacturing during the past ten years, because of its potential material and energy usage reductions. However, the development of the remanufacturing industry has been unsatisfactory because of little knowledge of its key industry indices. Many potential customers of remanufactured products do not trust the quality of remanufactured products. The major objectives of this paper are to classify the key industrial indices of the remanufacturing industry and to suggest future directions for improvements. To achieve these objectives, this paper used a combined method of grey incidence analysis and grey clustering, which are suitable for distinguishing critical industry indices that can measure the status of development situation of the remanufacturing industry. This approach was successfully applied to a case in Jiangsu Province, China, and consequently developed useful governmental and industrial policy recommendations for remanufacturing enterprises to promote that industry. The research results identified the “total number of employees with a master's degree or above”, the “total number of engineering and technical staff” and the “number of intermediate technicians” as the most appropriate industry indices to reflect the development situation of the remanufacturing industry in China. There are two more important findings. The first is that remanufacturing talents are the most important internal impetus of the remanufacturing industry and should be paid more attention to. The second is that investment in the remanufacturing industry does not have a strong positive correlation with industry characteristics. The “annual revenue of the remanufacturing industry” and huge investment have not played an effective role in promoting this industry so far. The main contribution of this paper is to provide an effective decision-making tool for defining key industry indices that have an important effect on the remanufacturing industry. The tool provides decision-makers a scientific basis for developing and implementing appropriate industry policies and improvement measures to expand the size and scope of the remanufacturing industry in the future.

Identifying key industry factors of remanufacturing industry using grey incidence analysis

Purpose The purpose of this paper is to identify most favorable (or quasi-preferred) industry characteristics of remanufacturing industry and most favorable (or quasi-preferred) industry factors which have an effect on these characteristics so as to improve these factors. Design/methodology/approach Grey system theory has prominent advantage of using few data and uncertainty information to analyze many factors. Therefore, it is more suited for system analysis than traditional statistical analysis methods like regression analysis, variance analysis and principal component analysis, which require massive data, certain probability distribution in the data and few variant factors. So in this paper, grey incidence analysis method, which is an important part of grey system theory, is used to identify industry characteristics and key industry factor of remanufacturing industry in China and then put forward appropriate industrial policies and countermeasures to improve these industry factors. Findings According to the results of this study, it reveals that there are no most favorable industry characteristics and no most favorable industry factors in remanufacturing industry of China. “Annual sale of remanufacturing industry” is identified as quasi-preferred industry characteristic, and “total number of employees with master degree or above in remanufacturing enterprise” is identified as the quasi-preferred industry factor. “Total building area of remanufacturing enterprise” is referred as the most unfavorable industry factors. Practical implications Judging from the findings of this study, four practical implications are summarized as follows: “annual sale of remanufacturing industry” should be given great importance because it is a quasi-preferred industry characteristic. “Total number of employees with master degree or above in remanufacturing enterprise” and “total number of research institution and university participated in remanufacturing” should be further strengthened by establishing an industry-university-research institute collaboration network, due to the fact that they are the top two quasi-preferred industry factors. “Total investment of remanufacturing industry” and “total annual R&D expenditures” have not played their due role in improving remanufacturing industry, so they should be moderately controlled so as to reduce waste of investment. “Total building area of remanufacturing enterprise” must be strictly controlled because of its little impact on remanufacturing industry. Originality/value In this research, grey incidence analysis is applied to identify key industry factors of remanufacturing industry for the first time. It helps in finding industry factors which are in urgent need of improvement and assists in making appropriate industrial policies and countermeasures to improve them by studying relationships between industry characteristic and industry factors.

Fault Diagnosis in Transformer Based on Weighted Degree of Grey Slope Incidence of Optimized Entropy

Dissolved gas analysis (DGA) is an important method to find the hidden or incipient insulation faults of oil-immersed power transformer. However, code deficiency exists in the gas ratio methods specified by the IEC standard and complexity of fault diagnosis for power transformer. Hence a new model based on optimized weighted degree of grey slope incidence was put forward. Firstly, the entropy weight is used to determine objective weight of indices; then the model fault types are obtained by weighted degree of grey slope incidence. The combination of entropy weight with grey slope incidence analysis can fully utilize over all information of DGA and give full play to the superiority of grey slope incidence, which overcomes shortcomings of original grey slope incidence analysis. The experimental results also demonstrate that the improved method has higher accuracy compared with three-ratio method and general grey slope incidence analysis method. The diagnosis accuracy is 92.8%.

Thermal Characteristic Analysis on a High Precision Turning Center’s Headstock

The performances of the high precision turning center will be influenced by the thermal characteristics of the headstock seriously, and accurately predict thermal characteristics of the headstock are helpful to improve the design level. The headstock of a high precision turning center produced by some plant has been regarded as the research objects of the paper. First the steady temperature distribution and thermal deformation of the headstock were calculated based the finite element analysis models of the headstock. Then the temperature sensitive points of the headstock were obtained by using the grey incidence analysis method. Finally the thermal error compensation model was built by using multiple linear regression method. The study lays a foundation for the thermal error compensation of the headstock of the turning center.

The Research of Gray Algorithm and Information Entropy in Route Planning Optimization

In order to solve the Unmanned Aerial Vehicle (UAV) 3-d track planning problems, according to UAV flight are subject to different threats, UAV flight track was established optimal decision-making system, and the fuel consumption, radar threats, missile threats, anti-aircraft threats and atmosphere threats are determined as the evaluation index of objective function, and optimal mathematical model of UAV flight track is constructed. Experience evaluation method is often used to Weight calculation, but there is certain subjectivity .Therefore information entropy method is adopted to determine the Weights by the set of track plans. Grey incidence analysis method is applied to deal with the gray correlation information between the various indicators and to solve the model. Finally, the optimal model is used to scheme selection for flight track planning problem with four threat radar points, five missile threat points, six artillery threat points and four climate threat points to the threat point of flight track planning scheme options. And get the flight track with the best overall performance and Minimum Comprehensive cost, the research provides a theoretical basis for further studying the three-dimensional UAV flight track optimization. DOI: http://dx.doi.org/10.11591/telkomnika.v10i8.1635 Full Text: PDF

Indoor Air Quality Audit and Grey Incidence Analysis of an Air-Conditioned Institutional Library in the Subtropics

The IAQ characteristics, both in terms of empirical objective measurements and subjective responses, are presented for an air-conditioned institutional library in subtropical climate. The objective measurements involve the measurement of physical parameters of the air dry bulb temperature, relative humidity, air velocity and the monitoring of the concentrations of selected chemical indicators of carbon dioxide, carbon monoxide, formaldehyde. The occupants' subjective sensation to IAQ is surveyed in terms of unacceptability. By calculating the relation degree between the subjective unacceptability and objective measurements with the grey incidence analysis method, the occupants' subjective sensation to IAQ is linked with the objective measured parameters and their relation is explored.

Research on Factors Influence of Vegetation Slope Protection Based on Grey Incidence Analysis Theory

Vegetation Slope Protection Engineering was affected by several factors, and has become the focus of the geotechnical engineering. The stability of the vegetation slope must be controlled rigorous according to the surrounding environment condition and safety level of the slope in highway. According to the Grey Incidence Analysis (GIA) method of grey system theory, a new grey theory model is applied in analyzing of the characteristics of Eco-engineering protected by roots of vegetation, to attain the correlation coefficient affected by extent of the factors. After analysis of several practical Bio-engineering examples, to attain the most influencing factors of the stability of vegetation slope are the density of roots (ρ), the length of roots (L), the diameter of roots (D), the weight of soil (γ), the anti-pulling force of roots (P), internal friction angle (φ), cohesive strength(c) and the shear strength of the soil (τ). The role of factors is classified in order to define the extent of the impact and provide guidance for construction and design of Eco-engineering. After analyzing the data collected from the field and several classicistic documents, utilized Grey Incidence Analysis method to make prediction in order to guarantee the slope safety. It shows that the grey system theory can be effectively and practically adopted in the slope stability analysis of vegetation slope in expressway and that has a good prospect.

Dynamical analysis on influencing factors of grain production in Henan province based on grey systems theory

Purpose – The purpose of this paper is to realize dynamical grey incidence order of influencing factors of grain production in Henan province using grey systems theory.Design/methodology/approach – Starting from choosing influence factors on grain production and dividing the 30 years (from 1979 to 2009 year) of grain production in Henan province into three periods, the authors calculate grey incidence degree between grain yield and every influencing factor by grey incidence analysis method, respectively, then obtain the grey incidence order of influencing factors in every period. Also based on the three grey incidence orders from different periods, the authors find a changeable tendency of influencing factors on grain production and key influencing factors on grain production in different periods. Finally, to keep Henan province grain production stable and sustainable, several policy suggestions are given.Findings – The results are convincing: it is effective and powerful to analyze dynamically influencin...