Grey Correlation Theory Research Articles

The sensitivity and timeliness of a variation correlation between structures in close proximity and located in the delta region

Typical geotechnical structures in the delta region include slopes, foundation pits, and embankments. An analysis of their interrelationships is essential for the overall safety and security of the delta region. At present, these structures are mainly studied by the manual analysis of single monitoring points and by inspection patrols performed by researchers in the field. However, this method is inefficient, costly, and risky to undertake. Furthermore, it is mainly through a time series that the respective states of a single-structure single monitoring point are successfully identified. This makes it difficult to present the correlation between structures and monitoring points, and makes it impossible to truly assess their overall safety patterns. To this end, this study proposes an intelligent analysis method based on feedforward neural networks to associate multiple monitoring points for multiple structures. It uses the correlation between the monitoring values of multiple geotechnical structures and multiple monitoring points for modeling. Then, key coefficients, the gray correlation theory, and degree of importance are introduced to assess the correlation and sensitivity factors of the changes occurring between different structures. The response time and duration between them were also analyzed. Finally, it was applied to a close, typical geotechnical structure system in South China, and the example application was good (R2: 0.91 ∼ 0.95, GR: 0.805 ∼ 0.981). The combined response time and duration of the M index of the foundation pit was optimal for the embankment S (Tr = 0, Tc = 3 ∼ 7) and the JM (Tr = 0, Tc = 4) index of the slope. The multi-correlation model established in this study provides new guidance for accurately revealing the latent hazard potential of typical geotechnical structural systems in the delta region in close proximity. It can also be used as a relevant implication for correlating changes between geotechnical structures in close proximity in other areas.

A Comprehensive Assessment of the Hydrological Evolution and Habitat Quality of the Xiangjiang River Basin

Human disturbance and climatic factors alter the hydrological state of rivers in many ways and have a degree of negative impact on the quality of watershed habitats; quantifying the impact of both human disturbance and climatic factors on hydrological change can help improve the quality of watershed habitats. Therefore, in this research, an integrated watershed assessment framework is proposed to analyse the watershed from four perspectives: hydrological situation, environmental flows, drivers, and habitat quality. A meteorological streamflow model based on the Long Short-Term Memory (LSTM) model was employed to analyse the hydrological evolution and quantify the influence of the drivers from the perspective of hydrological and environmental flows. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was then used to evaluate the spatial and temporal evolution of habitat quality in the basin. And, finally, the grey correlation theory was used to reveal the response of habitat quality to hydrological changes. Studies have shown that annual flow and precipitation are increasing in the Xiangjiang River (XJR) basin, while its annual potential evapotranspiration is decreasing significantly. After 1991, the hydrological conditions of the XJR were highly variable, with the combined rate of change of the most Ecologically Relevant Hydrological Indicators, ERHIs-IHA and ERHIs-EFCs, reaching 26.21% and 121.23%, respectively. Climate change and human disturbance are the main drivers of change for both (with contributions of 60% and 71%, respectively). Between 1990 and 2020, the habitat quality in the basin declined over time (from 0.770 to 0.757), with areas of high habitat value located mainly in mountainous areas and habitat degradation being concentrated in urban areas in the middle and lower reaches, gradually evolving towards areas of high habitat value in the periphery. There is a strong correlation between watershed habitat quality and the ERHIs. The results of the study can provide a scientific basis for maintaining regional ecological security and rational allocation of water resources.

Design of teaching quality evaluation system for higher vocational education based on data mining technology

Abstract It is advantageous for schools to realize exact education management, the cornerstone for developing abilities, by constructing higher vocational education teaching quality evaluation systems. The division of frequent item sets based on the modified Apriori algorithm under the association rule algorithm is used for the evaluation algorithm of this system to examine the evaluation data in the evaluation system, which is created in this work using data mining technology. Data validation was carried out from system performance and application analysis of association rules for the teaching quality evaluation system constructed in this paper. Regarding system performance, the highest response time of the system in this paper is 8.34s, which is about 56.94% and 40.68% shorter than that of the evaluation system based on AHP and gray correlation theory, respectively. This shows that using association rule algorithms can realize the operation of the evaluation system faster, improve evaluation efficiency, and use visual data to achieve precise education management in schools.

Experimental study on the disintegration characteristics of undisturbed loess under rainfall-induced leaching

Loess is prone to collapse as the soil approaches saturation, leading to severe geological hazards. However, how the undisturbed loess microstructure evolves due to rainfall-induced leaching is poorly understood and a detailed assessment of the corresponding disintegration characteristics is lacking. In this study, we conducted a series of leaching and disintegration tests on undisturbed Q3 loess from Yan’an, China. Loess disintegration on a macroscopic level were characterized using a self-developed disintegration apparatus, and the relationship with influencing factors such as moisture content, temperature, and salinity were explored. At the microscopic scale, scanning electron microscopy (SEM) was performed to qualitatively probe the underlying mechanisms of loess disintegration under varied leaching conditions. The microstructure properties of the loess samples revealed in the SEM images were examined using Image-Pro Plus (IPP) software. A quantitative relationship between the microstructural parameters of the pores and particles with disintegration was established based on the grey correlation theory. The results show that the disintegration process of undisturbed loess under the action of leaching can be divided into three stages: soaking, softening, and collapsing. Compared with samples without leaching, the study demonstrates that leaching can facilitate the loess disintegration. Under otherwise similar conditions, loess disintegration ratio decreases with increasing moisture content and salinity, whereas it increases with water temperature. In addition, microstructural observation shows that the undisturbed loess microstructure changed from interlocking to overhead with increased leaching, inducing favorable conditions for loess disintegration. Moreover, grey correlation analysis shows that the particle size distribution and macropore content of undisturbed Q3 loess yields a satisfactory correlation with the loess disintegration ratio. In general, rainfall-induced leaching effect is conducive to the disintegration of loess by degrading its internal structure.

Failure behaviour and damage evolution of multi-recycled aggregate concrete under triaxial compression

In this paper, the stress–strain behaviour, mechanical properties, characteristic stress, and damage evolution of multi-recycled aggregate concrete (Multi-RAC up to 3 recycling cycles) under triaxial compression were investigated, considering the effects of confining pressure and number of recycling cycles. Furthermore, a parametric sensitivity evaluation of key parameters using grey correlation theory to analyse the peak stress, peak strain, and elastic modulus of Multi-RAC. The results indicate that both peak stress and peak strain increase with rising lateral confining pressure. While the peak stress of Multi-RAC is lower than that of natural aggregate concrete (NAC), the deformation capacity of Multi-RAC is greater. The deformation and failure of Multi-RAC under triaxial loading can be categorized into five stages. Notably, crack initiation stress (σci) and crack expansion stress (σcd) demonstrate nonlinear growth as lateral confining pressure increases. In particular, the second generation of Multi-RAC (RACII) exhibits superior performance in resisting crack initiation and expansion, while the third generation of Multi-RAC (RACIII) performs relatively less favourably. The energy evolution characteristics and division of failure stages of Multi-RAC are effectively characterized by the evolution of elastic strain energy (Ue) and dissipation energy (Ud). The degree of progressive damage aligns with the increase in dissipation energy. Among the five key parameters, the number of recycling cycles shows the most significant grey correlation effect on the peak stress, peak strain, and elastic modulus of Multi-RAC. These findings contribute to a deeper understanding of the mechanical properties and failure behaviours of Multi-RAC under the complex triaxial loading conditions, thus promoting the application of Multi-RAC as a structural concrete.

Study on the mechanical properties and pore structure of granulated blast furnace slag self-compacting concrete based on grey correlation theory

ABSTRACT Variations in the mechanical properties and pore structure of granulated blast furnace slag self-compacting concrete were studied. The grey correlation theory established the relationship between mechanical properties and pore structure. The test results show that with the continuous improvement of age, the mechanical properties decreased with the increase of sand replacement rate in the early stage. In the middle and late stages, the compressive strength and splitting tensile strength of granulated blast furnace slag self-compacting concrete are higher than those of ordinary self-compacting concrete, while the elastic modulus continues to decrease with increasing slag content. After standard curing, the change in the pore structure parameters of ordinary self-compacting concrete is relatively stable. The pore structure parameters of granulated blast furnace slag self-compacting concrete change significantly. Because granulated blast furnace slag has a certain hydraulicity, the strength and strength growth rate of granulated blast furnace slag self-compacting concrete are higher than those of ordinary self-compacting concrete, and the corresponding pore structure parameters change. Through grey correlation analysis, the specific surface area and average chord length structure of granulated blast furnace slag self-compacting concrete are essential factors affecting its mechanical properties.

Spatial-temporal evolution and driving factors of ecological security in China based on DPSIR-DEA model: A case study of the Three Gorges reservoir area

Ecological security (ES) is an important element in the construction of an ecological civilization and plays a vital role in ensuring the sustainable development of social economies. Further, ES is an important measure of regional sustainable development. Based on ecosystem theory, this study constructs a comprehensive evaluation framework using the driving force-pressure-state-impact-response (DPSIR) and slacks-based measure of data envelopment analysis (SBM-DEA) models. Taking the Three Gorges Reservoir Area as an example, the study develops an ES evaluation system and realizes a transformation from “efficiency” to “quality”.Gray correlation theory and spatial autocorrelation and are adopted to analyze the ecosystem's spatial–temporal evolution and driving factors. The results demonstrate that the overall level of ES in the Three Gorges Reservoir Area from 2010 to 2020 was good; however, the spatial distribution of ES revealed an unbalanced state. The influence of each subsystem on the result of the ES evaluation is state > response > impact > driving force > pressure. The spatial correlation analysis of ES in the Three Gorges Reservoir area exhibited a positive autocorrelation, and the agglomeration effect was significant; on this basis, the key factors affecting ES were identified. The ratio of environmental protection investment, sewage treatment rate, green coverage rate of built-up areas, proportion of primary industry in GDP, and proportion of tertiary industry in GDP had notable effects on the ES of the study area. The research contributes to the theory of ES and provides guidance for ecologically sustainable development.

A procedure for risk assessment of check dam systems: A case study of Wangmaogou watershed.

Flood-based hydrodynamic damage to check dam systems on the Loess Plateau of China occurs frequently, and there is a strong desire to carry out risk assessments of such check dam systems. This study proposes a weighting method that combines the analytic hierarchy process, entropy method, and TOPSIS to assess the risk of check dam systems. The combined weight-TOPSIS model avoids weight calculation only considers the influence of subjective or objective preference and the bias of the single weighting method. The proposed method is capable of multi-objective risk ranking. It is applied to the Wangmaogou check dam system located in a small watershed on the Loess Plateau. The result of risk ranking matches the reality of the situation. The gray correlation theory model is utilized to rank the risks in the same research area and compared with the results of the combined weight-TOPSIS model. The combined weight-TOPSIS model is more favorable to risk assessment than the gray correlation theory model. The resolution level and decisive judgment of the combined weight-TOPSIS model are more advantageous. These results are in line with the actual conditions. It proves that the combined weight-TOPSIS model can provide a technical reference for the risk assessment of check dam systems in small watersheds.

Risk Assessment and Water Inrush Mechanism Study of Through-Type Fault Zone Based on Grey Correlation Degree

In order to effectively prevent and control the problem of water inrush from the through-type fault floor, based on the analysis of the case data of water inrush from the fault structure in the Fengfeng mining area, the types of karst water inrush from the floor are divided into 3 categories, 6 subcategories, and 17 fine categories. Four water inrush modes are summarized: composite structure water inrush, through-type fault water inrush, roof crack expansion water inrush, and floor vertical crack expansion water inrush. Based on the grey correlation theory and combined with the Analytic Hierarchy Process (AHP), this paper evaluates the water inrush risk of the F55-1 through-type fault zone from a micro individual perspective, taking the Xin’an Mine as the engineering background. Based on the water–rock coupling theory, the FLAC3D numerical simulation software is applied to study the disaster mechanism of the water inrush mode of the through-type fault. Through analyzing the changes of primary fracture stress and displacement of the intact floor strata and the aquifuge, and the pressure changes of confined water in fault zones, the collaborative water inrush mechanism of the damage and fracture of the bottom plate rock layer, the expansion and connection of the original fracture, and the seepage and progressive intrusion of the pressure water during the advancing process of the working face is analyzed. The research results indicate that the evaluation result of the water inrush risk of the F55-1 through-type fault in Xin’an Mine is Level I, belonging to the high risk and consistent with the actual situation model, verifying the rationality of the evaluation model. The process of water inrush in the numerical model is summarized as follows: a rock pressure failure zone is caused by the rupture and instability of floor aquifuge; a progressive intrusion zone develops—water inrush is connected between rock pressure failure zone and progressive intrusion zone; floor lagging flood occurs. Under the combined action of mine pressure and confined water pressure, the progressive intrusion height of confined water is significantly increased. The research results have important reference basis for future coal mining planning. This provides engineering reference and practical experience for the prevention and control of water damage in structured bottom plates under similar conditions.

Effect of dry-wet cycles on mechanical properties of polyurethane porous mixture

ABSTRACT Polyurethane porous mixture (PUPM) is a novel material with potential to extend the service life of pervious pavement. The porous structure makes the interior of the pavement material inevitably exposed to frequent cyclic action of environmental factors. However, the mechanical property decay behaviour of PUPM under the dry-wet cycles formed by water, air and corrosive ions is still unclear. Therefore, the mechanical properties of PUPM under different dry-wet cycles were characterised by Marshall stability, splitting strength and uniaxial compression strength tests. The variations in the microscopic properties of PUPM were investigated by computed tomography (CT), scanning electron microscopy (SEM) and Fourier transform infrared (FT-IR) spectroscopy. The grey entropy correlation theory was used to analyse the effect of variations in the functional groups of polyurethane on the mechanical properties of PUPM. It was concluded that the ageing of the polyurethane and the disruption of the bond at the binder-aggregate interface are the fundamental reasons for the mechanical property decay of PUPM. The influence of each functional group on the mechanical strength of the PUPM is in this descending order: amino groups linked to the carbonyl groups, carbonyl groups, ether bonds, methylene groups, and amino groups formed hydrogen bonds with water.

The Road of Post-Industrialization Transformation in Developing Countries Based on Weighted Markov and Grey Correlation Theory, Taking the Change of Industrial Structure in Heilongjiang Province of China as a Case Study

In the context of economic globalization, the comparative advantages of developing countries and developed countries tend to be more complex. After the economic crisis in 2008, the challenges of developing countries are intensified, and the game is more cyclical; Especially in the critical period when the “Fourth Industrial Revolution” is pending, many countries have increased their efforts in policy formulation and efficiency improvement, focusing on industrial transformation and upgrading, and closely combining structural reform with the industrialization process. Therefore, it is particularly important to analyze, change and forecast the industrial structure of post-industrial regions in developing countries based on data science algorithms, and to reshape the understanding of the adjustment of the world economic order and the evolution of the international trade division system. Based on the proportion of gross regional product and output value of three industries in Heilongjiang Province of China from 2001 to 2020, the minimum deviation model of industrial structure in Heilongjiang Province is constructed through Markov theory. The Lingo software is used to obtain the transition probability matrix of the industrial structure state, and combined with the autocorrelation coefficient of each order and the transfer weight, the change trend of the proportion of the output value of the three industries and the change of the contribution rate of the three industries (to GDP) in Heilongjiang Province in the next 10 years are obtained; At the same time, through the grey correlation index and spss software, this paper analyzes the correlation changes between the three industrial adjustments and economic development in Heilongjiang Province in the past 20 years, discusses the new growth points of economic development in Heilongjiang Province and puts forward corresponding suggestions for the adjustment of different industrial structures in Heilongjiang Province, and finally extends the general rules of the development of post-industrialization in the world. This article believes that it is necessary to adjust the structure of the first, second, and third industries reasonably based on different historical and natural endowments, contemporary backgrounds, and other practical factors, in accordance with local conditions, circumstances, and each with its own emphasis. At the same time, it also requires the support and inclination of government policies; Adapting industrial structure to local economic development while actively leading productivity and local economic development.

Analysis of global temperature influencing factors based on spearman correlation coefficient method and grey correlation theory

In recent years, mankind has experienced the hottest period in its history as greenhouse gas concentrations have increased. As a hot topic for many years, the issue of global warming is gaining more and more attention.By exploring and analyzing the main factors affecting global temperature, we can take targeted measures to improve the global warming situation.In this paper, firstly,by building the ARMA model, we found that the global average temperature is increasing year by year.Secondly, we analyze that latitude and longitude are negatively correlated with global average temperature and time is positively correlated with global temperature by Spearman's correlation coefficient method, and year, CO2, population, forest area, land area, wetland area are all correlated with global temperature by gray correlation theory method, and the gray correlation of year, CO2 and land area is over 0.9.Finally, we give some effective suggestions to improve global warming,such as expanding forest area and reducing carbon emissions.

Performance evaluation of an auto-cascade refrigeration system using grey correlation theory and response surface methodology

This article focuses on evaluating and analyzing the performance of an autocascade refrigeration system with the zeotropic mixture of R600a/R1150/R14 refrigerants using grey correlation theory and response surface methodology (RSM). The correlation degree among various factors is analyzed using grey correlation theory. The interactive influences that have significant impacts on the six output parameters are illustrated, and a regression model is further validated by five confirmation parameters. The results show that the vapor quality of the evaporator outlet is the greatest factor that affecting the refrigerating capacity and coefficient of performance (COP). However, the evaporation temperature has the greatest effect on compressor’s discharge temperature, pressure ratio, exergy destruction rates, and exergy efficiency. Lower vapor quality of the condenser outlet and condensation temperature can improve the performances of refrigerating capacity, COP, compressor’s discharge temperature, compression ratio, total exergy destruction rate, and exergy efficiency based on the RSM results. The random five groups of validation parameters indicate that the errors between the predicted modeling and calculation results are all less than 5%, demonstrating that the RSM model has good predictability. The results achieved in this work will assist in the optimizing analysis and the application of cryogenic refrigerators.

Prediction of global temperature based on the BP neural networks

The problem of global warming is getting worse as global temperature has risen year by year to an alarming level. This paper is first based on historical data on global temperatures, two prediction models were developed using Gray Prediction Method and BP Neural Network model, whose results show that the root mean square error test value of BP neural network is about 0.03 lower than that of the gray prediction method (0.1627).Thus, the BP neural network prediction model is proved effective, and then the model was analyzed by gray correlation theory, which found that carbon dioxide concentration, forest cover area and human population are affecting the global temperature, and the Gray correlation of the fisrt two factors is as high as 0.8, which makes the two the main factors. In the end the paper gave measures to contain global warming.

Performance of rice husk ash under different two periods combustion conditions and effect of particle size on the strength of mortar

This study aims to investigate the effect of two periods burning conditions on the chemical properties of rice husk ash (RHA). Gray correlation theory analysis combined with a scanning electron microscope was used to precisely analyze the impact of RHA particle sizes on the mechanical properties and microstructure of mortar. The experimental results reveal that prolonging residence time at 600 ºC could significantly reduce the carbon content and boost the silica content in RHA. The potassium content of RHA could be reduced by burning at a low and then high temperature. Additionally, gray correlation analysis indicated that the particle sizes of 5 -10 μm in RHA could positively accelerate the gaining strength of mortar, followed by 10-15 μm and < 5 μm. At the micro-scale, incorporating RHA with a mean particle of 5.9 μm could accelerate the formation of calcium silicate hydrates having a low Ca/Si by secondary hydration reaction, subsequently leading to the increment of mortar strength.

A gray correlation based Bayesian network model for fault source diagnosis of multistage process – Small sample manufacturing system

Fault source diagnosis methodology is one of the key technologies of quality control and assurance for multi-source & multi-stage manufacturing processes, especially in small sample manufacturing systems. By analyzing the existing research on fault source diagnosis methods, a Bayesian network-based methodology is proposed. Gray correlation theory and mechanism analysis method are used in the process of Bayesian network model construction to reduce the dependence of sample data size for structure learning in the process of small sample manufacturing of complex products. In addition, two fault source diagnosis methods based on manufacturing principle analysis and reverse Bayesian network respectively are proposed. The strategy of the combined use of the two methods in the actual manufacturing scenes is given to cope with the fault source diagnosis scenario in the real manufacturing process. In the end, an example from an actual factory is provided to validate the effectiveness and efficiency of the proposed model and methodologies.

Investigation on the Mechanical Properties and Strengthening Mechanism of Solid-Waste-Sulfur-Based Cementitious Composites.

This research used waste ceramic powder (CP) to replace aggregate, fly ash (FA) as filler, and combined them with sulfur to prepare composite cementitious materials. The variations of the mechanical properties with the aggregate proportions (aggregate mass/total mass) of 65%, 70%, and 75%, and the FA contents (FA mass/aggregate and filler mass) of 0%, 10%, 20%, 30%, 40%, and 50% were studied. The correlation evaluation model of sulfur content, CP content, FA content, and mechanical properties was established using the gray correlation theory, and the comprehensive mechanical property evaluation model was established as the foundation of the entropy method. Finally, the optimum proportion of the solid-waste-sulfur-based cementitious composites was determined. Results showed that, without FA, the CP increased from 65% to 75% and the comprehensive mechanical properties of the specimen increased by 60.53%. After FA was added, the peak point of the comprehensive mechanical properties appeared in group S75F10, which was 0.9210. During the hardening of the cementitious material, sulfur was mainly used as a binder, CP played the role of skeleton and part of the filler, whereas, as a crystal nucleus, the FA promoted the transformation of the sulfur crystals. Both the CP and FA can reduce the porosity of the specimen to a certain extent and have potential defect repair ability, thus densifying the matrix and improving the strength. When the proportion of sulfur: CP: FA is 1:2.7:0.3, the flexural (FS), compressive (CS), and splitting tensile (STS) strengths of the specimen are 14.8, 86.2, and 6.8 MPa, respectively. The flexural (FCR) and tensile (TCR) compression ratios are 0.172 and 0.079, respectively.

Research and development suggestions on the coordinated development of green cities based on spss data processing basis

Based on extensive reading of domestic and international research on green city development, this paper uses a combination of qualitative and quantitative methods to conduct an in-depth study of the interactive and coordinated development of a city PRED and its model from the perspective of systemic analysis based on grey correlation theory, and then evaluate the green city development of a city. Based on PRED system theory, we analyze the deep meaning of green city and clarify the interaction between them and the guiding significance of PRED system theory for green city development. Design a city green city evaluation index system, use gray correlation analysis method, and build a gray correlation evaluation model of green city coordination ability of a city based on PRED system analysis. This paper has researched and thought about the coordinated development of green cities based on the basic data processing. The optimization and re-planning study was carried out on the development strategy of the previous period. The future urban development of Wei has laid some research theoretical foundation.

Study on the Low Temperature Cracking Mechanism of Steel Slag Asphalt Mixture by Macroscale and Microscale Tests

Steel slag’s physical and mechanical properties are close to natural gravel, which can replace natural aggregate with paving asphalt mixture pavement. Based on macro- and microscales, it is necessary to study the low-temperature cracking characteristics of steel slag asphalt mixture (SAM). This paper aims to study the low-temperature cracking characteristics and influence mechanism of steel slag asphalt mixture by macro- and microscale tests. This article analyzes the strain field distribution and cracks propagation law of SAM at low temperatures by the three-point bending test combined with digital image correlation (DIC). The microscopic pore characteristics of SAM were studied by nuclear magnetic resonance (NMR). Based on fracture mechanics and weight function theory, the variation law of the stress intensity factor at the crack tip of the asphalt mixture with crack propagation is derived. The correlation between microscopic pores and low-temperature cracking characteristics of asphalt mixture was analyzed based on the grey correlation theory. The results show that SAM has more small and less large pores, and its total porosity is lesser than that of the basalt asphalt mixture (BAM). The initial elastic stage of SAM resisting bending deformation is longer than that of BAM, the bending strain energy density (dW/dV) is larger, and the crack penetration is slower. The horizontal strain energy density (DE) of SAM is greater than BAM, and the crack tip stress is greater. The porosity correlates well with the low-temperature crack resistance of the asphalt mixture.

Gray correlation analysis of factors influencing compressive strength and durability of nano-SiO2and PVA fiber reinforced geopolymer mortar

AbstractTo investigate the mechanical properties and durability of nano-SiO2, polyvinyl alcohol (PVA) fiber-modified fly ash (FA), and metakaolin (MK)-based geopolymer mortar (FMGM), tests of compressive strength, electrical flux, freeze–thaw cycles, and sulfate dry and wet cycles were conducted. Based on the experimental results, combined with Dunn’s gray correlation theory analysis method, a mathematical analysis of the effect sensitivity of the contents of the four mixtures on the mechanical properties and durability of FMGM was carried out. The method of gray correlation analysis can solve the mathematical problem with partial unclear and uncertain information, and the method requires less data and less computation compared with other mathematical analysis method. The results showed that the gray correlation degree between the content of MK and the electric flux value is higher than the that of other comparison sequence and each reference sequence, while the gray correlation degree between the PVA fiber dosage and the loss rate of compressive strength is lower than that of other comparison sequence and each reference sequence. The influence of the four mixture contents on the compressive strength and mass loss rate was in the following decreasing order: MK and FA, PVA fiber, and nano-SiO2. In addition, the influence of the four material mixture contents on the electric flux value and compressive strength loss rate was consistent in the following decreasing order: MK and FA, nano-SiO2, and PVA fiber. Furthermore, the mechanical properties and durability reached the optimum when the PVA fiber content was 0.6% and the dosage of nano-SiO2was 1.0%. The results of this study can provide a new method for the analysis and evaluation of mechanical properties and durability of nano-SiO2and PVA fiber-reinforced FMGM in future.