Grey Relational Analysis Theory Research Articles

Measurement and prediction of the relationships among the patent cooperation network, knowledge network and transfer network of the energy storage industry in China

The commercialization process of energy storage patents affects the development of the energy storage industry. Clarifying the relationships between the characteristics of the applicants and patent transfer can facilitate technology transfer. In this study, China’s energy storage patent data from 2009 to 2021 were divided by the rolling period. Based on this, the patent cooperation network, knowledge network, and transfer network were constructed via social network analysis. The analysis reveals the following. First, the number of industry-university-research institutions that jointly apply for patents is increasing, and the knowledge field is also expanding. Cooperation and transfer activities are more frequent in the eastern developed regions of China. Second, by using grey relational analysis theory, it was found that the degree centrality, closeness centrality, and clustering coefficient of the cooperation network are closely related to the transfer network. Compared with the cooperation network, the energy storage knowledge network has a more significant relationship with the transfer network. The knowledge elements stock of patent transferor and transferee is more relevant to patent transfer activity than the patent stock. This also proves that the knowledge and cooperation networks are decoupled. Additionally, patent applicants for energy storage patents should focus not only on their past average locations to maintain the competitive advantage, but also on future location trends to seize development opportunities. Finally, the proposed recommendations can help applicants facilitate patent transfer activities in the energy storage industry by adjusting the location of the network.

Grey Correlation Analysis between Macro Mechanical Damage and Meso Volume Characteristics of SBS Modified Asphalt Mixture under Freeze-Thaw Cycles

The effect of freeze–thaw (F–T) in the seasonal frozen area would lead to damage to asphalt pavement. After water enters asphalt pavement, the water in voids would expand at a lower temperature, which could change the void content and number, affecting the macro mechanical properties of the asphalt mixture. The rapid development of CT scanning and digital image processing (DIP) provides powerful technical support for the research of asphalt mixture meso volume characteristics. In this paper, the mechanical properties of basalt fiber reinforced asphalt mixture subjected to F–T cycles were tested at different temperatures to clarify the decay law of mechanical properties under F–T cycles. Then, the meso images of the asphalt mixture under various F–T cycles could be obtained by using CT tomography. Based on DIP technology, the meso characteristic parameters of CT images for asphalt mixture were extracted, and the development of asphalt mixture freeze–thaw damage was further analyzed. The test results showed that with the F–T cycle, the macro mechanical properties of the asphalt mixture rapidly declined in the early stage of the F–T cycle and gradually tended to be flat. There would be serious damage inside the asphalt mixture in the late stage of the F–T cycle. The damage to the mechanical properties of the asphalt mixture under the F–T cycle can be attributed to the change in the internal mesostructure of the asphalt mixture. Based on the grey relational analysis theory, the formation of the connected void was the main factor affecting the damage in the early stage of the F–T cycle, while the formation of new voids mainly affected the later development of F-T damage.

Effect of interfacial transition zone on creep behavior of steel fiber-reinforced concrete

• A SFRC creep prediction model considering ITZ was established. • The role of ITZ in SFRC was revealed. • The effects of relevant factors on SFRC creep were analyzed. • The key factors affecting SFRC creep were determined. To explore the interface transition zone (ITZ) effect on the creep behavior of steel fiber-reinforced concrete (SFRC), this study proposed a three-phase creep prediction model based on the mesomechanical shear lag theory. The model verification was performed using available creep data, and three influencing factors were analyzed. The proposed creep prediction model well described the creep behavior of SFRC, revealing the ITZ's role in it. The specific creep values of SFRC at the loading age of 365d with 1, 2, and 3% steel fiber contents exceeded those assessed without the ITZ effect account by 9.8, 6.3, and 54.0%, respectively. The effects of the ITZ elastic modulus and thickness, as well as the steel fiber length-to-diameter ratio on the SFRC creep, were analyzed via the proposed model. The grey relational analysis theory can characterize the correlation between related factors and various variations, so as to determine the key factors. Through this theory, it was revealed that the ITZ elastic modulus variation had the most significant effect on the SFRC creep.

Evaluation of Surrounding Rock Quality of Tunnels Using a Combined Method of Weighted Norms Based Grey Relational Analysis and Fuzzy Mathematics Theory

Evaluation of Surrounding Rock Quality of Tunnels Using a Combined Method of Weighted Norms Based Grey Relational Analysis and Fuzzy Mathematics Theory

Quality Evaluation of Three Kinds of Hickories Based on Grey Relational Analysis and Entropy-Weight Theory

In this paper, the nutritional ingredient, aroma component, and texture of three kinds of hickories, including American hickory, Chinese Linan hickory, and Chinese Hunan hickory, were tested by instruments. The quality of different hickory varieties was analyzed at three levels by using the grey entropy correlation analysis, namely, the single nutrient composition analysis; nutritional composition and texture analysis; nutrient composition, texture, and aroma analysis. Through the analysis of nutritional composition, American hickory gets the highest score (80.6945), followed by Linan hickory (74.9987), and Hunan hickory has the lowest score (58.5925). Through the analysis of nutrition composition and texture, Linan hickory has the highest score (80.89), American hickory is the second (71.77), and Hunan hickory is last (61.62). Through the analysis of nutrition composition, texture and aroma, Linan hickory has the highest score (75.91), followed by American hickory (74.17), and Hunan hickory has the lowest score (64.20). Finally, the comprehensive evaluation of Linan hickory quality index score is the highest. The main factors contributing to the high score of Linan hickory include superior fatty acid spectrum, aminogram and higher initial chewing hardness, moderate crispness of secondary chewing, optimal palatability, and unique aroma components ((S)-2-methyl-1-butanol, 3-methyl-2-pentene, (+/−)-2-methylbutyric acid methyl ester ethyl butyrate, ethyl 2-methylbutyrate, methyl phthalate, decene, (1S)-(−)-β-pinene). The research results provide a basis for consumers to understand the quality differences of different hickories.

Analyzing the Sustainability of Water-Cultural Industry and Their Influencing Factors in China

This study is an empirical analysis of China’s “sustainable development ability of water cultural industry” based on the attributes of water cultural industry (economic attribute and cultural ideology). First, using “factor analysis” and “grey relational analysis theory,” establish an indicator-system for the level of sustainable development of the cultural industry, then quantify the relationships between the water cultural industry and its influencing factors, and finally, propose some solutions for enhancing the sustainable development of the water cultural industry from the perspective of “improving resiliency.”

Mesomechanical creep model of fly ash-contained cement mortar considering the interfacial transition zone and its influential factors

A mesomechanical model was proposed to predict the creep behavior of cement mortar containing fly ash, with the Laplace transform principle applied. In this model, the mortar was regarded as a composite material, which is composed of the elastic fine aggregate phase, the viscoelastic cementitious paste phase, as well as the viscoelastic Interface transition zone (ITZ) phase between them. The generalized self-consistent Mori-Tanaka model in the Laplace transform domain was used as a base to establish the prediction creep model of mortar. The results showed that the proposed creep model of mortar considering the ITZ properly simulated the mortar creep behavior, with the coefficient of variation between the modeled and measured values locating in the range between 3% and 5%. Parameter analysis based on the grey relational analysis theory was conducted to clarify the key factors in this proposed model. Regarding the sensitivity of mortar creep to the factors, the decreasing order was as follows: ITZ viscoelastic parameter > ITZ thickness > fine aggregate volume fraction > the fineness of aggregate.

The Application of the Strength Reduction Shortest Path Method to the Stability Analysis of Shallow Buried Tunnel

To improve the theoretical analysis of surrounding rock stability of shallow buried tunnels. The strength reduction shortest path theory is applied to the stability analysis of shallow buried tunnel surrounding rock, combined with the ultimate equilibrium strength reduction theory. We discussed the influence of the depth and span ratio of tunnel, cohesion, and internal friction angle on the shortest path of the strength reduction, and studied the effects of various factors on shallow buried tunnel safety relationship by using strength reduction factor of safety and the shortest path of the shallow buried tunnel surrounding rock and the grey relational analysis theory. The results show that: in the analysis of shallow buried tunnel in strength reduction, the approximate distribution obeys parabolic between reduction path length and the reduction ratio. When the strength reduction of cohesion is the shortest path the reduction rate is greater than the internal friction angle. The internal friction angle and cohesive force have a great influence on the stability of shallow tunnels under the method of shortest path of strength reduction. Finally, the comprehensive safety factor of shallow buried tunnels calculated by the finite element strength reduction shortest path method is greater than that calculated by the limit equilibrium method.

Picture fuzzy set-based decision-making approach using Dempster-Shafer theory of evidence and grey relation analysis and its application in COVID-19 medicine selection.

To offer better treatment for a COVID-19 patient, preferable medicine selection has become a challenging task for most of the medical practitioners as there is no such proven information regarding it. This article proposes a decision-making approach for preferable medicine selection using picture fuzzy set (PFS), Dempster–Shafer (D–S) theory of evidence and grey relational analysis (GRA). PFS is an extended version of the intuitionistic fuzzy set, where in addition to membership and non-membership grade, neutral and refusal membership grades are used to solve uncertain real-life problems more efficiently. Hence, we attempt to use it in this article to solve the mentioned problem. Previously, researchers considered the neutral membership grade of the PFS similar to the other two membership values (positive and negative) as applied to the decision-making method. In this study, we explore that neutral membership grade can be associated with probabilistic uncertainty which is measured using D–S theory of evidence and FUSH operation is applied for the aggregation purpose. Then GRA is used to measure the performance among the set of parameters which are in conflict and contradiction with each other. In this process, we propose an alternative group decision-making approach by the evidence of the neutral membership grade which is measured by the D–S theory and the conflict and contradiction among the criteria are managed by GRA. Finally, the proposed approach is demonstrated to solve the COVID-19 medicine selection problem.

Similarity evaluation of stratum anti-drilling ability and a new method of drill bit selection

Considering the stratum anti-drilling ability, drill bit working conditions, drill bit application effect and drill bit economic benefits, the similarity of stratum anti-drilling ability was evaluated by grey relational analysis theory to screen out candidate drill bits with reference values. A new comprehensive performance evaluation model of drill bit was established by constructing the absolute ideal solution, changing the relative distance measurement method, and introducing entropy weight to work out the closeness between the candidate drill bits and ideal drill bits and select the reasonable drill bit. Through the construction of absolute ideal solution, improvement of relative distance measurement method and introduction of entropy weight, the inherent defects of TOPSIS decision analysis method, such as non-absolute order, reverse order and unreasonable weight setting, can be overcome. Simple in calculation and easy to understand, the new bit selection method has good adaptability to drill bit selection using dynamic change drill bit database. Field application has proved that the drill bits selected by the new drill bit selection method had significant increase in average rate of penetration, low wear rate, and good compatibility with the drilled formations in actual drilling. This new method of drill bit selection can be used as a technical means to select drill bits with high efficiency, long life and good economics in oilfields.

Research on Service Quality Evaluation Model of Medical Institutions Based on Dempster-Shafer Evidence Theory— Taking Jiangsu Province, China as an Example

From the perspective of patients and medical insurance agencies, the paper used the fuzzy rough set method to select the indexes and established the service quality evaluation index system of medical institutions. Using Dempster-Shafer evidence theory to synthesize the subjective weights and the objective weights, the combined weights of the evaluation indexes were obtained. Combining grey relational analysis and Dempster-Shafer evidence theory to establish a regional medical service level evaluation model in an asymmetric environment. The model can accurately identify the quality of medical service in various regions. We can compare and analyze the service quality of medical institutions in various regions from different dimensions, and provide a theoretical basis for each region to formulate policies related to the rational allocation of medical resources.

Retracted] Internet of Things Security Detection Technology Based on Grey Association Decision Algorithm

This paper analyzes the current real‐time monitoring system based on grey‐related IoT security sensors for the detection of risk factors in the production environment of the Internet of Things and proposes a design plan for the Internet of Things environment monitoring based on the grey‐related Internet of Things security sensor network, and according to the reliability guarantee mechanism of the system, a three‐dimensional uniform IoT node deployment method suitable for IoT security monitoring is proposed. Based on the grey correlation analysis, it can provide a quantitative measurement analysis for the development and change state of a system, which is very suitable for the analysis of dynamic operating systems. As a real‐time dynamic system of the Internet of Things, the use of grey correlation method to analyze its network security status has good operability and practical value. According to the multisource information processing technology, the monitoring data are preprocessed by dynamic limiting filtering, and then the data are fused at the data level with the optimal weighting algorithm. Through the use of grey correlation analysis to quantify the relative impact of cyberattacks on the network within a certain period of time, the quantitative assessment of the security environment and status of the entire network is realized. Finally, the characteristics of grey relational analysis and rough set theory attribute reduction are used to form the basis of grey correlation decision‐level fusion algorithm, to achieve effective processing of the data of the Internet of Things security monitoring system.

Application of fuzzy logic and grey based Taguchi approach for additives optimization in expansive soil treatment

In this paper, grey relational analysis (GRA) and fuzzy logic were successfully combined with Taguchi optimization method and utilized on multiple quality responses to optimize ternary additives for the improvement of expansive soil properties. The ternary additives included sawdust ash (SDA), quarry dust (QD) and ordinary Portland cement (OPC) additives. Signal-to noise ratios were estimated for each of the quality characteristics and then normalized using the GRA theory. The normalized values, which were set as the input variables in the fuzzy logic system, were used to obtain the output multiple performance characteristic indices (MPCI). Thereafter, factors level effect on the MPCI were evaluated and the factor level that maximized the averaged MPCI was selected as the optimal factor level. The optimum combination of the ternary additives (20% SDA+20%QD+8%OPC) was obtained subsequently. Confirmatory experiments and micrograph analysis were executed and the results obtained reveal the effectiveness of the applied optimization procedure.

A model for evaluating green credit rating and its impact on sustainability performance

The development of economic activities and social progress index leads to the governmental considerations for the environmental challenge’s issues. The Green Credit Policy (GCP) in China for manufacturing, as a part of a sustainable finance package, initiatives restrictions with suppliers to reduce harmful pollution for the environment. The study mainly validates the impact of GCP on manufacturing for diminishing the emerged pollution to the environment. The study develops Neutrosophic Multiple-Criteria Decision-Making Framework (N-MCDMF) according to neutrosophic theory and various MCDM methods of grey relational analysis (GRA), analytic network process (ANP), the Decision-Making Trial and Evaluation Laboratory technique (DEMATEL), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to support the decision-makers with highly systematic procedures in the uncertain and inconsistent environmental conditions. The N-MCDMF evaluates the conditions of GCP and recommends the optimal Supply Chain Management (SCM) in manufacturing alternatives. A case study is presented for the validation of the issues of applicability and flexibility for the proposed N-MCDMF. The results obtained from the implementation of the N-MCDMF indicates the applicability and flexibility of the proposed approach. In addition, results show that SCM in manufacturing can provide more cooperation for the environment to reduce harmful pollution and to attain sustainability for achieving motivations under the restrictions of GCP.

An evaluation method of synthetic force engineering support capability based on multi-level grey system

Engineering support operations are characterized by diverse tasks, dispersed regions, complex command coordination, many points, long lines and wide areas. It has been difficult to model and evaluate its capability comprehensively. In this paper, according to the characteristics, the index system of support capability of synthetic Force project is constructed, and the support capability of synthetic Force project is analysed and evaluated by combining multi-level grey relational analysis theory and AHP. An evaluation method is put forward and verified by an example. Compared with the past models and methods, they are simple to operate, applicable and scientific in conclusion. It is convenient to analyze and compare the support capacity of multiple units. It can provide support and basis for the development of engineering support capacity construction and scientific assessment of synthetic Force.

Research on Prediction Model of Cable Line Cost Based on Least Square Support Vector Machine

With the development of China’s economy and society, the total social electricity consumption has risen dramatically, and the investment scale of transmission and transformation projects has increased accordingly. Cable line engineering is a kind of power transmission and transformation engineering, which is buried deep underground, has complex construction conditions and high cost. Compared with substation engineering and overhead line engineering, its cost control is more difficult. In order to facilitate the fine management of cable line cost, this paper analyses the influencing factors of cable project cost based on grey relational analysis theory, uses principal component analysis method to reduce the dimension of influencing factors, and establishes a cable line cost prediction model based on least squares support vector machine method. It can guide the economic evaluation of investment decision of cable line project. The results show that the accuracy of the cost prediction model based on least squares support vector machine method can reach 95.06%. The research in this paper is innovative and practical.

Vibration-intensity prediction of underwater blasting based on grey relational analysis and dimension theory

In addition to the distance from the blasting center and the charge amount, the influence of the water depth of the blasting zone and the difference in elevation between the measuring points are non-negligible for the vibration intensity of underwater blasting. Hence, the conventional Sadov’s formula is no longer fully applicable for the vibration-intensity prediction of underwater blasting. Combined with the vibration data of underwater blasting projects, a grey relational analysis of the influencing factors for blasting-vibration intensity has been conducted. The obtained order of the influence degree, from high to low, is the charge amount, elevation of the measuring point, water depth of the blasting zone, and the distance from blasting center. A formula for vibration-intensity prediction that comprehensively considers the influencing factors was derived from dimension theory; this formula is similar to Sadov’s formula. The comparison of the two prediction results showed that the average error of the formula considering the water depth of the blasting zone and the difference in elevation was below 10%. This showed a significant improvement in the prediction accuracy, compared with the Sadov’s formula, indicating that this derived formula is applicable for the vibration-intensity prediction of underwater blasting on land measuring points.

Analysis on the tourism resource evaluation factors based on grey relational analysis – Taking Guizhou minority areas as an example

Evaluation of tourism resources can help the government adjust policies and foster the development of tourism. As one of the ethnic areas, Guizhou has abundant tourism resources. In this study, five tourism resources in Guizhou, a minority area, including Huangguoshu Falls, Qianhu Hmong Village, Qi ngyan Ancient Town, Hailongtun Tusi Town and One Hundred Miles Azalea Park, were evaluated by using grey relational analysis theory (GRA). Through the establishment of the evaluation system, the appropriate evaluation indexes were selected and evaluated by the expert group to obtain index weight and specific index value. After dimensionless processing of the data, the relevancy coefficient and relevancy degree were calculated by grey relational analysis. It was found that the relevancy degree of the five tourism resources were 0.6907, 0.6329, 0.6421, 0.6129 and 0.6785 respectively, which indicated that the values of Huangguoshu Falls and One Hundred Miles Azalea Park were high and tourism value of Hailong Tusi Town was relatively low, and the results obtained were consistent with the actual situation.

Research on Investment Demand Forecast of Power Grid Based on Grey System Theory

The forecast of power grid investment demand is of great significance for reasonably arranging the investment of power grid construction funds and reducing the cost of funds. In this paper, a forecasting model of power grid investment demand based on grey system theory is proposed. Firstly, the correlation coefficient method is used to analyze the correlation between the investment demand of power grid and its influencing factors, and the key factors affecting the investment demand of power grid are selected. Then the grey relational grade analysis theory is used to construct the investment demand forecasting model of power grid. The validity and rationality of the model are verified by an example of power grid investment prediction in a certain area. The model is of great theoretical and practical significance for the coordination of power grid investment and the scientific planning of power grid investment scale.

Identification of unbalanced bids based on grey-fuzzy evaluation method

To provide theoretical reference for owners to identify unbalanced bids, this paper aims to construct an identification method based on grey relational and fuzzy set theory. Firstly, to measure the closeness degree between bidding unit price from engineering’s estimated price, grey relational analysis theory is used to express the relationship between them. Secondly, a combined weight method determining all line items is calculated through integrating analytic hierarchy model and maximizing deviation method. Thirdly, based on fuzzy set theory, the membership degree and the fuzzy relation matrix are constructed, and then a fuzzy comprehensive identification method is established to identify unbalanced bidding. Fourthly, on the basis of fuzzy comprehensive identification method, the scoring set and total score vector are designed, and the rank of unbalanced bids is obtained by total score vector. Finally, a practical construction project bidding is stated to illustrate the effectiveness and practicability of the proposed method.