Grey Correlation Analysis Method Research Articles

The relationship between pore structure and strength of aeolian sand concrete under low temperature

To examine the relationship between microscopic parameters and compressive strength of aeolian sand concrete (ASC) at low temperatures, the compressive strength of ASC at different temperatures is predicted by factors such as the pore structure parameters and the ambient temperature. The experiments used 100 % replacement of river sand (RS) with aeolian sand (AS) to prepare fully ASC, and regular concrete with the same water-cement ratio as the control group. The experiment used nuclear magnetic resonance (NMR) technology and grey correlation analysis method to analyze the microscopic parameters and compressive strength of concrete specimens with three curing ages of 7d, 28d, and 60d at temperatures of 20 °C, 0 °C, −5 °C, −10 °C, −15 °C, and −20 °C. It was shown that the agglomeration between the fine particles during the mixing process results in a large number of pores in the interior of the ASC, resulting in a larger porosity compared to ordinary concrete. As a result, its compressive strength was lower than that of ordinary concrete, and the loose and porous internal structure provides room for the filling of more ice crystals. Therefore, the increase in compressive strength of ASC at different curing ages in an environment of −20 °C was greater than that of ordinary concrete. Among them, at-20 °C, the compressive strength of ASC with curing ages of 7d, 28d and 60d increased by 6.31 %, 3.59 % and 3.97 % respectively compared with ordinary concrete. Finally, a predictive model between parameters such as temperature, porosity, mean pore size distribution and gel content and compressive strength was developed, which was highly accurate.

Analysis of the Grey Correlation Between Higher Education and Economic Development

Regional higher education and economic development are inseparable, so it is of great significance to study the correlation degree between higher education and economic development. This paper integrates the relevant evaluation indexes, and uses the grey correlation analysis method to explore the degree of mutual influence between higher education and economic development in Guangxi. The results show that the gross product of primary industry, per capita disposable income of urban residents and urbanization rate are the key factors affecting the level of higher education; the Di-Clark theorem is not applicable to the industrialization development of Guangxi; the increase of institutions and full-time teachers and the investment of education funds are the main driving force for higher education to promote economic development. Finally, to provide policy suggestions for the high-quality development of higher education and economy in Guangxi.

How are nature-based solutions contributing to the improvement of ecosystem quality in China: A systematic review

Nature-based solutions (NbS), an upgraded version of ecological restoration concept, has developed as an integrated approach to encompass a broad range of actions that protect, restore, or sustainably manage ecosystems to provide benefits to people. However, it is challenging to obtain a thorough understanding of the effectiveness of NbS because of the uncertainty of the assessment in different regions based on ecosystem services. Here, we conduct a synthesis analysis of the effects of ecological interventions on ecosystem quality within China. We systematically analyze 76 studies selected from 275 peer-reviewed papers, which were undertaken at regional scale and published between 2011 and 2022. Average values of ecosystem services before and after the ecological interventions are extracted to quantify the ecosystem changes. Results show that ecological restoration purposefully contributes to the improvements of ecosystem services with an increase in Net Primary Productivity (NPP) of 31% and an increase in soil conservation (SC) of 21%. Effects on water yield (WY), carbon storage (CS) and habitat quality (HQ) are all not significant. Restoration interventions have a mixed effect on ecosystem service trade-offs which may vary by regions. Trade-offs primarily exist between WY and other ecosystem services on the Northeastern Forest Belt and the Southwestern Karst, while synergies mainly exist among NPP, SC and CS on the Loess Plateau and the Qinghai-Tibet Plateau. Moreover, utilizing grey correlation analysis methods, factor analysis reveals that temperature and precipitation are highly correlated with the changes of the five ecosystem services. Natural factors contribute more to the changes of NPP, SC and WY than the human factors. This research is aimed at obtaining an overall perception of the effectiveness of ecological restoration programmes implementation in different regions across China, which will provide references for reducing ecosystem services trade-offs and adjusting the layouts of regional ecological restoration programmes.

Analysis of the coupled and coordinated development of sports and tourism industries and the driving factors

The Yellow River Basin has a wealth of tourism resources, a long history of folk sports, and strong legislative support, all of which are advantages for the growth of the sports tourism sector. This study constructs an evaluation index system based on panel data from nine provinces and regions in the Yellow River Basin from 2011 to 2020, and then measures the development index and analyzes the driving factors using the entropy method, coupling coordination degree model, kernel density estimation method, and grey correlation analysis method. The findings demonstrate that (1) the Yellow River Basin's overall level of growth in the sports and tourist sectors exhibits a consistent and upward trend and that Shandong and Henan provinces clearly have an edge over other provinces in terms of development. (2) The geographical development pattern was lower Yellow River > upper Yellow River > middle Yellow River, and the coupling coordination status shifted from slight disorder to good coordination. (3) There is a close connection between sports tourism and variables including population density, financial prowess, and infrastructure growth. The employment population index has the smallest link with invention patent authorization. The macro-policy framework should therefore be strengthened in the future, the sports tourism infrastructure should be improved, and the Yellow River basin's unique sports tourism resources should be fully utilized in order to increase brand influence. In addition, new sports tourism products should be developed in response to market demand and consumer preferences, and enterprise innovation and research and development efforts should be increased in order to achieve high-quality development transformation.

Research on Fatigue-Healing Performance of Asphalt Mixture Based on the Semicircular Bending Test.

In order to study the self-healing performance of macroscopic fractures of asphalt mixtures, semicircular bending (SCB) tests were used to test 90# base asphalt mixtures, SBS (Styrene-Butadiene-Styrene) modified asphalt mixtures, and SBS + CR (Chloroprene Rubber) composite modified asphalt mixtures. The F-H-F (the asphalt mixture specimen was fatigued for a certain number of times, then healed under certain conditions, and then fatigued until destroyed) test was carried out, and the fatigue life recovery rate of the fatigue test before and after healing was defined as the healing index (HI). The gray correlation analysis method was used to judge the influence degree of influencing factors on fatigue-healing according to the correlation index. The results show the type of asphalt has the most significant influence on the healing ability of the asphalt mixture. In the case of complete healing, the fatigue-healing performance of the SBS + CR composite modified asphalt mixture was the best, followed by the SBS-modified asphalt mixture, and 90# base asphalt. When the healing temperature is close to the softening point of asphalt, the healing performance of 90# base asphalt is better when the healing temperature is low. When the healing time is longer, the healing performance is better, and there is an optimal healing time. The healing index decreased with the increase in the degree of damage. When the degree of damage is too large, the asphalt mixture will be difficult to heal.

Research on Influencing Factors of Electricity Consumption in China Based on Grey Theory and Big Data Technology

With the development and application of computer theory, electronic information technology, economics and other disciplines, more and more models are being used to discuss electricity consumption factors. Thesis based on actual data of China, this paper discusses the influence of economic growth, electricity price, urbanization level, industrial structure, science and technology investment level and opening degree on electric power consumption level of our country, and analyses the influence of grey correlation analysis method. To drive electricity consumption, the first is to optimize and upgrade the industrial structure, and the second is to further improve the level of urbanization. The research results of this paper have certain reference value for relevant managers and government departments to formulate policies.

Evaluation of teaching quality of universities in the context of big data for the cultivation of application-oriented talents

Abstract Exploring the evaluation of the teaching quality of colleges and universities for applied talent cultivation in the context of big data is to be able better to improve the teaching level of colleges and universities. In this paper, the multi-indicator evaluation method is explained, and the commonly used teaching quality evaluation methods, i.e. hierarchical analysis, entropy weight method and gray correlation analysis, are cited. The basic principle of the hierarchical analysis method is given, the initial weight calculation steps of AHP method are illustrated, and the initial weights of AHP method are combined and solved using the entropy weight method. The evaluation principle of the gray correlation analysis method is given, and the combined weights of the AHP-EWM evaluation are illustrated using the gray correlation analysis method. Finally, universities’ teaching quality evaluation indexes for applied talent cultivation were constructed using the AHPEWM evaluation method, and the indexes were mined and analyzed respectively. From the indicators of theoretical literacy and professional research ability, the overall evaluation of the teaching quality of colleges and universities is 92.77% above the C grade. From the indicators of innovation practice and moral quality, the percentages of students’ evaluation of teaching quality in colleges and universities with A, B, C and D grades are 49.02%, 28.6%, 5.12% and 7.25%, respectively. This shows that the evaluation of teaching quality in colleges and universities is multifaceted, and colleges and universities can improve their teaching level according to different evaluation factors.

The Influence Factors of Incremental Forming Geometric Accuracy based on the Weighted Gray Correlation Analysis Method

In view of the process complexity of the pillow effect phenomenon, the orthogonal experiment was designed, and the numerical simulation of the single-point incremental forming process under various process parameters was carried out by using the finite element software. Taking the height of the specific position (i.e., bulging) of the pillow effect phenomenon as the evaluation index, the data were analyzed based on the weighted gray correlation analysis method. The influence of the forming height, sheet thickness, forming angle, layer feed, tool head diameter, and part size process parameters on the forming geometric accuracy was studied. The optimal process parameters of single-point incremental forming and the primary and secondary order of the influence on the evaluation index were obtained. The results show that the weighted gray correlation analysis can effectively reduce the geometric error of the pillow effect phenomenon form of the target part and improve the forming accuracy.

Effects of the different phase change materials on heat dissipation performances of the ternary polymer Li-ion battery pack in hot climate

To improve the heat dissipation performance of the Ternary Polymer Li-ion Batteries(TPLBs) in hot climate, a heat dissipation method including different PCMs (Paraffin, 10% GNP + Paraffin, 10% EG + CPCM) was established, and orthogonal test and fuzzy grey correlation analysis method were applied to investigate the heat dissipation effects of the TPLBP in hot climate. The results shown that the TPBP with 10% EG CPCM is of heat dissipation characteristics and thermal security (namely the temperature difference is less than 5K), it makes sure the safety operation of new energy vehicles under 3C in hot climate. And the fuzzy grey correlation values between the thermal conductivity λ of the PCM and the time τ0 of melting point appearance of the PCM in the TPLBP is of a maximum value of 0.5660, and the fuzzy grey correlation values between the discharge current I and the time τ0 of melting point appearance of the PCM in the TPLBP is of a minimum value of 0.3386. Therefore, the discharge current I has the greatest effect on the liquid phase composition ω of PCM, but also has the least effect on the time τ0 of melting point appearance of the PCM in the TPLBP.

Multiplex Quantitative Analysis of 9 Compounds of Scutellaria baicalensis Georgi in the Plasma of Respiratory Syncytial Virus-Infected Mice Based on HPLC-MS/MS and Pharmacodynamic Effect Correlation Analysis.

According to traditional Chinese medicine, Scutellaria baicalensis Georgi possesses the therapeutic properties of heat-clearing, dampness-drying, diarrhea alleviation, and detoxification, making it a clinically used remedy for respiratory infections. The objective of this study was to investigate the changes in constituent content, pharmacodynamic effects, and material basis of Scutellaria baicalensis Georgi in the plasma of mice infected with respiratory syncytial virus (RSV). The results showed that a sensitive and efficient high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS) method was established in this study. Multiple quantitative analyses of Baicalein, Apigenin-7-glucuronide, Baicalin, Oroxylin A 7-O-beta-d-glucuronide, Wogonoside, Norwogonin, Wogonin, Chrysin, and Oroxylin A in mouse plasma revealed a bimodal absorption phenomenon within the time frame of 0.167 h to 6 h post-administration, with the exception of chrysin. Following 6 h of administration, the concentrations of 9 components continued to decrease until they became undetectable. In comparison to the model group, all administered groups exhibited significant reductions in lung index and viral load, with their lung index repair rate and viral suppression rate aligning with the blood concentration-time curve. Finally, through the application of the gray correlation analysis method, we identified Baicalein, Baicalin, Oroxylin A 7-O-beta-d-glucuronide, Wogonoside, Norwogonin, and Wogonin as potential pharmacodynamic material bases of Scutellaria baicalensis Georgi against RSV infection.

Reaction heat effect and change characteristics of key groups in coal-oxygen intrinsic reaction path.

The intrinsic reaction of coal with oxygen in the process of low-temperature oxidation is the main reaction path leading to self-heating and spontaneous combustion of coal. Most of the existing studies regard the coal oxidation as an overall reaction, ignoring the multi-path characteristics of coal low-temperature oxidation, and it is difficult to accurately explore the intrinsic reaction characteristics between coal with oxygen. Therefore, the low-temperature oxidation process of coal was studied by using a C80 microcalorimeter and in situ FTIR technology from the macro and micro levels. The "profile subtraction method" was used to study the coal-oxygen intrinsic reaction process, and the reaction heat effect and the change characteristics of key functional groups in the process were analyzed. Furthermore, the gray correlation analysis method was used to study the relevant characteristic parameters in the reaction process and grasp the essential structure-activity relationship. The experimental results show that, compared with the overall reaction process in air atmosphere, the change in the heat release of the coal-oxygen intrinsic reaction path has changed to different degrees, and the change in the slow oxidation stage is the most significant (the heat absorption decreases by 70.1-90.9%). In addition, the characteristic temperature points show different degrees of advance, of which the initial exothermic temperature point is the largest (about 21-46 °C), which directly leads to a significant shortening of the slow oxidation stage (30.1-47.4%). The changes of functional groups in the intrinsic reaction path are more regular. With the increase of temperature, the oxygen-containing functional groups -C=O and the aliphatic hydrocarbon functional groups -CH2- and -CH3 showed a fluctuating trend of increasing and decreasing, respectively. The oxidation heat-contributing functional groups of coal are mainly related to the degree of metamorphism and the functional group reaction characteristics during the reaction. With the deepening of coalification degree, the main heat-contributing functional groups as a whole showed the change rule of oxygen-containing functional groups → aliphatic hydrocarbon functional groups → aromatic hydrocarbon functional groups. In addition, the change of -OH content in the three coal samples has a high correlation with the change of the total heat release of coal.

Prediction of the Height of Fractured Water-Conducting Zone: Significant Factors and Model Optimization

Predicting the height of the fractured water-conducting zone (FWCZ) can be challenging due to their significant grey characteristics and the difficulty in scientifically selecting relevant influencing factors. To address this issue, we utilized the Pearson correlation analysis method and the grey entropy correlation analysis method to identify the significant factors and their degree of correlation with the height of FWCZ. Based on this, several constructed models were optimized, and the reliability of the best regression model was verified through parameter inversion analysis. The results indicate that the spatial distribution differences of the main coal mining seams contribute to the complex and variable occurrence conditions of coal seams. This is an important factor that contributes to the significant gray characteristics in predicting the height of FWCZ in the study area. A modeling approach has been proposed for predicting the height of FWCZ. This method is based on analyzing significant factors and conducting a multi-level evaluation of the selected prediction models. The order of correlation between significant influencing factors and the height of FWCZ is as follows: comprehensive hardness of overlying rock > average thickness of sandstone > mining depth > mining height. The results of the multi-level evaluation analysis show that, when using small sample high-quality datasets, the GA-Catboost algorithm has better prediction accuracy compared to the MSR and GA-BP algorithms. The results of the parameter inversion analysis for the GA-Catboost regression prediction model indicate that within the mining height range of 2.5–5.5 m, the ratio of fractured/mining height in the main coal seams is primarily concentrated between 20.45–30.59. In addition, a prediction method was developed to determine the limiting mining height by considering water conservation in coal mining. The relevant research results can provide fundamental theoretical support for ensuring safety in underground production and protecting groundwater in mining areas.

Fabrication of Microcolumn Arrays Using Through-Mask Electrochemical Micromachining on the 42CrMo Alloy Steel

Studies have shown that surface texture can improve lubrication state and reduce friction and wear. The cold pressing process of micro-units can prepare surface textures at low cost, in large quantities, and with high efficiency, but the micro-pillar array mold required for the cold pressing process is difficult to prepare. In this study, the influence of mask electrochemical processing parameters on the height and height uniformity of the micropillar array was studied by orthogonal experiment on the 42CrMo alloy steel. Four main factors are designed in the orthogonal experiment, namely voltage, duty cycle, frequency, and mask spacing, and each factor is set to three levels. The results of the range analysis show that: voltage and duty cycle are positively correlated with the height of the microcolumn, but negatively correlated with uniformity, and when the duty cycle is 50%, the uniformity of the microcolumn decreases sharply; The height and uniformity of the microcolumns increase with the increase of mask spacing. The height of the microcolumn is positively correlated with the frequency, and the uniformity of the microcolumn first increases and then decreases with the increase of frequency. Therefore, in order to meet the height and uniformity requirements at the same time, the grey correlation analysis method was used to obtain the optimal processing parameters: 35 V (voltage), 30% (duty cycle), 300 um (spacing), and 5 kHz (frequency). The average height of the microcolumns prepared by this parameter is 57.632 um and the microcolumn has excellent high uniformity.

Ecological and navigational impact of the construction and operation of the Qingyuan dam

Dam construction has important impact on the ecological environment and navigation conditions of a river. Therefore, evaluating the degree of impact of such engineering constructions and seeking the optimum management are vital. This study considered the example of the construction of the Qingyuan Dam on the Beijiang River (China). The flow condition was calculated using a two-dimensional hydrodynamic model, and a habitat suitability model and navigation risk indicators were used to conduct quantitative assessment of the impact of different scenarios. The spawning ground habitat of Megalobrama terminalis was taken as an ecological measurement index. The gray correlation analysis method was used to quantify the influence of four flow indexes (i.e., water surface slope, backflow, flow velocity, and water depth) on navigation safety. The simulation results showed that construction of the Qingyuan Dam had serious negative impact on the ecological environment in the dry season, but that dry season navigation conditions have been improved greatly. Following construction of the dam, with increase in the Feilaixia Hydro-junction discharge, the ecological and navigable usable area both first increased and then decreased. With comprehensive consideration of the usable area and the spatial distributions of habitat suitability and navigation risk, when the Feilaixia Hydro-junction discharge is 3000 m3/s and the water level in front of the Qingyuan Dam is 10 m, the ecological and navigation benefits of the studied river reach were determined to be optimal. These research results could provide guidance for the management of the Feilaixia–Qingyuan river section, and help deliver optimum ecological and navigational benefits.

Evolution and Influencing Mechanisms of the Yili Loess Mechanical Properties under Combined Wetting-Drying and Freeze-Thaw Cycling.

Landslides frequently occur in the loess-rich Yili region of Xinjiang, China, due to the combined effects of wetting-drying and freeze-thaw (WD-FT) cycles, which cause changes in the soil/loess internal structure and shear strength. This paper explores the combined effect of WD-FT cycles on the shear strength evolution of Yili loess through cyclic and triaxial shear tests. The micromechanism of the effect of WD-FT cycles on the loess properties is studied through scanning electron microscopy tests. Finally, the gray correlation analysis method assesses the correlation between relevant macro and micro parameters. The results show that: (1) With the increase in WD-FT cycles, the cohesion of loess decreases first and then gradually stabilizes, while the internal friction angle first grows and then drops before stabilizing. This indicates that the WD-FT cycles cause different degrees of decline in the soil's internal friction angle and cohesion. (2) As the number of WD-FT cycles increases, the average abundance and directional probability entropy fluctuate slightly, gradually decreasing and stabilizing. In contrast, the particle size dimensionality gradually decreases and stabilizes, and the pore area ratio first increases and then gradually stabilizes. (3) Six microstructural parameters (average diameter, average abundance, particle size dimensionality, directional probability entropy, particle roundness, and pore area) are selected for correlation analysis with the shear strength index of loess. The results show that the particle size dimensionality closely correlates with macroscopic internal friction angle under coupled cycling, while the pore area closely correlates with macroscopic cohesion. These findings are instrumental in preventing and controlling loess landslides caused by WD-FT cycles in the Yili region of Xinjiang, China, and similar loess-rich regions.

Research on Displacement Efficiency by Injecting CO2 in Shale Reservoirs Based on a Genetic Neural Network Model

Carbon dioxide injection can help solve two issues in shale reservoir production. Firstly, it can reduce carbon emissions while, secondly, improving unconventional reservoir recovery. There are many controlling factors for CO2 injection to enhance oil recovery in shale reservoirs, and the effect of field implementation varies greatly. The key to popularizing this extraction technology is determining the main controlling factors of CO2 displacement efficiency. Using CO2 shale displacement laboratory results, the grey correlation analysis method was used to determine the main controlling factors affecting core oil displacement efficiency, such as shale reservoir physical parameters (rock compressibility, porosity, median pore size, matrix permeability, TOC, and oil saturation) and engineering parameters (soaking time and injection pressure). The genetic algorithm (GA) was introduced to optimize the backpropagation (BP) neural network to construct the prediction model of the CO2 indoor displacement experiments in shale cores. The results showed that the injection pressure among the engineering parameters, the CO2 soaking time among the gas injection parameters, and the porosity among the shale physical parameters were the main controlling factors affecting the oil displacement efficiency. The prediction accuracy of the genetic neural network model improved, and the coefficient of determination (R2) reached 0.983. Compared with the conventional neural network model, the mean absolute error (MAE) was reduced by 30%, the root mean square error (RMSE) was reduced by 46%, and the R2 increased by 11%. Optimizing the learning and training of the prediction model significantly reduces the cost of laboratory experiments. The deep-learning model completed by training can intuitively show the degree of influence of input parameters on output parameters, providing a theoretical basis for the study of CO2 displacement mechanisms in shale reservoirs.

Analysis of Efficiency Differences and Research on Moderate Operational Scale of New Agricultural Business Entities in Northeast China

Various new agricultural business entities in China are important business organizations to improve agricultural production and management efficiency, and to promote the professional and large-scale development of agriculture. Exploring the efficiency differences of different business entities and the importance of moderate management scale in promoting the modernization of agriculture development has important practical significance. Based on the theory and method of system engineering, this study takes the main grain production areas of Northeast China as an example, and analyzes the efficiency differences of various new agricultural business entities by using the survey data of agricultural business entities and data envelopment analysis. Moreover, it applies the DEA-GA-BP prediction model and the entropy method (gray correlation analysis method) to study the moderate scale of agricultural business entities. The results show that there are certain efficiency differences among new agricultural business entities, among which the family farm has the highest average cross-efficiency value, and the best operational scale of the family farm is when the land cultivation area input is 9015~10,000 mu. The most optimal ranges of its production input factors are obtained, but the performance of the technical efficiency of family farms needs to be improved. Based on this, it is proposed that the focus of the construction of new agricultural business entities should be on family farms, with the best ratio of production factors for reference, constantly optimizing the allocation structure of production factors on family farms and strengthening the effective application of advanced production technologies on family farms.

Evaluation of Reconstruction Potential for Low-Production Vertical Wells of CBM in the Southern Qinshui Basin

Production practice has shown that not all low-production coalbed methane (CBM) wells can be reconstructed into high-production wells through secondary stimulation, so it is necessary and timely to establish an evaluation index system, form an evaluation method, and evaluate the reconstruction potential of low-production wells. Based on the development practice of CBM in the southern Qinshui Basin, this paper analyzes the influencing factors of low production in vertical wells from the aspects of coal and rock reservoir conditions, drilling and completion engineering, and drainage engineering. It is proposed that the evaluation of the reconstruction potential of low-production wells should focus on the quality of CBM resources, the difficulty of CBM desorption and diffusion, and the degree of damage to coal reservoirs caused by the initial reservoir stimulation. Twelve parameters, including gas content, gas saturation, reservoir pressure gradient, critical desorption–reservoir pressure ratio, and permeability, were systematically selected as evaluation indicators, and the grading reference values for each evaluation indicator were comparatively given. Then, a multi-factor comprehensive evaluation method for the reconstruction potential of low-production wells based on gray correlation analysis method was established. The reconstruction potential of low-production wells was divided into three levels: high, medium, and low. When reconstructing low-production wells, it is recommended to prioritize the low-production wells with high reconstruction potential, followed by those with medium reconstruction potential, while low-production wells with low reconstruction potential are not recommended for reconstruction. Finally, the evaluation method was used to evaluate the reconstruction potential of five low-production wells in a CBM block, and suggestions for the reconstruction order and reconstruction potential levels for each well were given.

Research on the relationship between defense technology innovation and high‐quality economic development: Gray correlation analysis based on panel data

AbstractBased on panel data from 2010 to 2019, this study examines the relationship between defense science and technology innovation and high‐quality economic development at the provincial level in China. Using the gray correlation analysis method of panel data and an evaluation index system of high‐quality economic development, we calculate the gray correlation coefficient and decompose its time‐series gray correlation degree and cross‐sectional. Our findings indicate that the correlation between defense science and technology innovation and high‐quality economic development in China is generally stable during 2010–2019. However, Beijing stands out as an exception with a correlation coefficient of less than 0.5. Furthermore, there is regional gray correlation heterogeneity with the smallest correlation degree found in the eastern region and the largest in the northeast region. Based on our results, we propose three countermeasure suggestions: first, to balance national defense construction and economic construction; second, to optimize national defense science and technology strategy according to local conditions; and third, to effectively utilize industrial structure advantages. In summary, our study contributes to the literature by highlighting the relationship between defense science and technology innovation and high‐quality economic development in China. Our findings provide implications for policymakers and practitioners to make informed decisions in achieving sustainable and high‐quality economic development.

Grey correlation analysis on influencing factors of Yang deficiency constitution

ObjectiveTo explore the influencing factors of Yang deficiency constitution in traditional Chinese medicine (TCM) from the perspective of mathematics with the use of calculation formulas, so as to protect patients from getting diseases caused by Yang deficiency constitution and provide suggestions for TCM disease prevention. MethodsBased on the classification and determination criteria of TCM constitution implemented by China Association of Chinese Medicine, data for 24 solar terms from May 5, 2020 (Start of Summer) to April 20, 2021 (Grain Rain) for the identification of Yang deficiency were collected by mobile constitution identification system. The grey correlation analysis method was used to determine the grey correlation degree of the factors influencing Yang deficiency constitution. In addition, a random forest model was constructed for the verification of the results from the grey correlation analysis, and for the evaluation of correlation degree between Yang deficiency constitution and its influencing factors. ResultsA total of 16 259 sets of data were collected from healthy or sub-healthy individuals aged from 18 to 60 years living in the central and northeastern parts of Sichuan Province (China) for the identification of TCM constitutions. After screening and preprocessing, a total of 544 sets of data for the identification of Yang deficiency constitution, involving 18 aspects of factors influencing Yang deficiency constitution. The results of the grey correlation analysis showed that there were 12 influencing factors whose grey correlation degree with Yang deficiency constitution was greater than 0.6. The accuracy of these 12 influencing factors with the training set and validation set of the Yang deficiency constitution random forest model were 98.39% and 93.12%, respectively. ConclusionIn the sample data selected in this paper, grey correlation analysis is the appropriate technology to analyze the influencing factors of Yang deficiency constitution. It provides a new idea and a new methodological reference for the research and analysis of the influencing factors of TCM constitution.