Grey Correlation Analysis Research Articles

Optoelectronic effect of Al-based buffer layers on Al-doped ZnO thin transparent conductive films on flexible substrates

AZO (Al-doped ZnO) film is a transparent conductive film that offers a simple preparation process, low cost, non-toxicity, and excellent stability. It serves as a high-quality material extensively used in liquid crystal displays, solar cells, and other fields. In this study, AZO thin films were prepared on a PET substrate with an Al2O3 buffer layer using the magnetron sputtering method. The deposition parameters were optimized through the Taguchi method and Grey Correlation Analysis. The results demonstrate that the optimal deposition parameters for achieving superior photoelectric properties during the fabrication of AZO films are 100 W (radio frequency power), 1.0 Pa (sputtering pressure), 20 min (coating time), and 20°C (substrate temperature). Furthermore, the incorporation of an Al2O3 buffer layer enhances the quality of AZO film on PET substrate. This investigation successfully deposited uniform and highly efficient AZO thin films onto flexible PET substrates at low temperatures, thereby expanding their potential applications in flexible electronics.

Study on optimization of thermal injection parameters in fractured reservoirs of HDR

ABSTRACT To improve the heat recovery of hot dry rock (HDR) and realize the efficient and sustainable development of geothermal energy, it is necessary to analyse the factors affecting the heat recovery performance of HDR fractured reservoir. In this paper, a numerical model of heat recovery in fractured reservoirs with HDR is established. The effects of injection parameters on the heat recovery performance of the Enhanced Geothermal System (EGS) are compared and analysed by means of the average temperature, heat extraction rate, production temperature and heat recovery power of matrix rocks at different locations. The influence degree of injection flow rate and injection temperature on production temperature was analysed by grey correlation analysis method. The results showed that reducing the injection temperature is beneficial to fully extract the heat energy in the rock mass. The injection flow rate is positively correlated with the heat extraction rate and negatively correlated with the extraction temperature. In this simulation scheme, the optimal results are as follows: injection temperature is 298.15K, injection flow is 12 kg/s, and the influence of injection flow on production temperature is greater than that of injection temperature. This study provides a theoretical basis for the development and utilization of geothermal energy in HDR and provides a reference for the design of engineering operation parameters.

Optimization of Magnetic Field-Assisted Laser Cladding Based on Hierarchical Analysis and Gray Correlation Method

Process parameters directly affect the quality of laser cladding. In this study, magnetic field-assisted laser cladding experiments were carried out on the surface of 300 M ultra-high-strength steel by setting laser energy density, magnetic field strength, and frequency as processing parameters. The optimization of laser cladding process parameters was investigated based on evaluating the quality of the laser cladding layer through hierarchical analysis and gray correlation analysis. Based on orthogonal test data, the correlation coefficients of the process parameters with the single objective function and the correlation degree of the multi-objective function were calculated by using the gray theory. Then the comprehensive objective optimization was carried out according to the gray correlation degree. The optimization problem with multiple process objectives was transformed into a single gray correlation degree optimization method to realize the optimization of process objectives and obtain the optimal combination of process parameters. The validation experiments indicate that the quality of the laser cladding layer can be greatly improved by employing optimal process parameters. The optimized laser cladding layer shows a reduced microstructure size and enhanced wear resistance, indicating the effectiveness of the optimization approach.

Effective passenger flow congestion propagation model for multi-mode rail transit networks

ABSTRACT During peak passenger flow periods, congestion propagation directly affects the operational safety and efficiency of multi-mode rail transit interconnections. By analyzing the key factors affecting congestion propagation, such as the train stop schedule, and considering parameters such as the basic reproduction number and propagation threshold, this study proposes a multi-mode rail transit susceptible-infected-recovered-susceptible (MRT-SIRS) epidemic model to analyze passenger flow congestion propagation. Simulation experiments and sensitivity analyses using data from the multi-mode rail transit in Beijing, China, were conducted to examine the influence mechanism of key factors on congestion propagation. The degree of influence of each factor was investigated using Gray correlation analysis. Each key factor, including the propagation and recovery rates, influences congestion propagation differently. The results of this study may provide theoretical support for the efficient operation and management of multi-mode rail transit systems.

Characterisation of surface morphology of high voltage DC relay contacts under arc erosion

Abstract High voltage DC relays are a crucial component in new energy vehicles. Due to the high failure rate caused by contact sticking (fusion welding), existing technologies can only analyze contact morphology after failure. There is an urgent need to determine the quantitative characterization value of contact surface morphology and the correlation between morphology, failure mechanisms, and working conditions. In this study, an Olympus DSX1000 microscope is used to extract surface topography data, and a quantitative topography characterization method based on a machine vision system is proposed to quantitatively analyze contact surface changes after arc erosion. Grey correlation analysis was applied to explore the relationship between electrical parameters such as voltage, current, and capacitance, and the contact morphology features. The results show that current and capacitance have the greatest influence on contact surface features after arc erosion, while voltage has a relatively smaller influence. This conclusion is consistent with the experimentally observed arc erosion features. Finally, an arc ion sputtering deposition model was developed to analyze the material transfer mode and its influence on the contact failure mechanism. The results provide a scientific basis for the analysis and design improvement of high voltage DC relays.

Based on Spectrum-Effect Relationship, Network Pharmacology, and Molecular Docking, the Material Basis and Mechanism of Antioxidant Effect of Miao Medicine Indigofera stachyoides Lindl Were Studied.

Indigofera stachyoides Lindl (IS.Lindl, Xuerensen in Chinese) is a traditional medicine frequently utilized by ethnic minorities; nevertheless, the chemicals responsible for these effects have not been identified. Ultraperformance liquid chromatography (UPLC) was utilized to establish the fingerprints of various origins. Free radical scavenging in 1,1-diphenyl-2-trinitrophenylhydrazine (DPPH) and 2,2-biazobis(3-ethyl-phenylpropylthiazole-6-sulfonate) diammonium salt (ABTS) assays was used to evaluate the antioxidant activity. Partial least-squares regression analysis (PLSR) and gray correlation analysis (GRA) were utilized to determine the spectral-effect relationship in order to screen the antioxidant pharmacodynamic components. The corresponding targets were obtained from Traditional Chinese Medicine Systems Pharmacology (TCMSP) and Integrated Traditional Chinese Medicine (ITCM). Disease-related targets for antioxidants were collected from GeneCards and Online Mendelian Inheritance in Man (OMIM) databases. The PPI interaction network analysis, GO enrichment analysis, and KEGG pathway analysis were established using the online analysis platform, and Autodock software assisted in aligning the components with important targets. The fingerprint profile revealed 32 common peaks, and eight standards were identified using standard comparison, with similarity ranging from 0.920 to 0.995. The primary antioxidant components include proanthocyanidin B1, epicatechin, and proanthocyanidin B3. Important targets include EGFR, CASP3, IL6, PTGS2, and TNF. Important signaling pathways include the AGE-RAGE signaling pathways in diabetic complications, the MAPK signaling pathway, the IL-17 signaling pathway, and the pathways in cancer. The results of molecular docking technology showed that the main active ingredients of the drug could bind well to the core target. In this study, we successfully established the spectral-effect relationship of IS.Lindl and clarified the effective substances of IS.Lindl. Through network pharmacology and molecular docking methods, it was clear that IS.Lindl plays an antioxidant role through multicomponent, multitarget, and multipathway synergy.

Evaluation system of vocational education construction in China based on linked TOPSIS analysis

In response to the task of vocational education reform in the new era, in order to cultivate innovative skilled talents, it is necessary to improve traditional evaluation methods to enhance their efficiency. This study proposes an evaluation model for vocational education construction that combines grey relational analysis and approximate ideal point method (TOPSIS). By selecting indicators and combining subjective analytic hierarchy process and objective entropy weight method for weight allocation, the weights of the indicators are determined using subjective analytic hierarchy process and objective entropy weight method. Through experimental analysis, the results showed that among the 11 analysis indicators, the weight of policy environment indicators was the highest at 0.124, while the weight of employment rate and contract signing rate indicators was the lowest at 0.050. The above results indicate that the TOPSIS comprehensive evaluation system based on grey correlation analysis has better application effects in practical scenarios and is more suitable for the development requirements of vocational education.

Simulation of lunar soil compressive strength performance test based on grey correlation analysis

Detecting water ice in the permanent shadow area of the lunar south pole is an important task of China's Chang'e-7. For this purpose, a simulation study was carried out under the earth environment, and a test sample of polar water-containing simulated lunar soil was prepared. The mechanical properties of the lunar soil simulant were tested under ultra-low temperature conditions, and the changes in water content, relative density, temperature, loading rate, and base material ratio with compressive strength were analyzed. The results show that the compressive strength of the frozen lunar soil simulant increases with the increase of water content, increases with the increase of density, and increases with the decrease of temperature. It is less affected by the change of loading rate. The order of compressive strength affected by different base material ratios is: 100%anorthosite, <90%anorthosite, +10%basalt <70%, +30%anorthosite <100%, basalt, lunar soil simulant. Finally, the correlation between the basic physical properties of lunar soil simulant such as water content, relative density, temperature, loading rate, and ratio and compressive strength is explored through grey correlation analysis. The correlation order is: water content> density> temperature> ratio> loading rate. This paper prepared and tested the mechanical properties of hydrated lunar soil, and proposed a more systematic and standardized implementation plan. It serves as the basis for studying the properties of hydrated lunar soil in the polar region, and provides a theoretical basis and reference for subsequent lunar soil simulation research.

VMD-HPCA-GRU ultra-short-term wind power forecasting based on COOT algorithm

In order to improve the prediction accuracy of ultra-short-term wind power, a combined prediction model of variational mode decomposition (VMD), hierarchical principal component analysis (HPCA) and gated recurrent unit neural network (GRU) based on COOT algorithm optimization is proposed. Firstly, the energy difference method is used to determine the number of sub-modes of variational mode decomposition, so that the original power sequence with strong nonlinearity is decomposed into a group of relatively stable sub-modes. Secondly, the correlation value between high-dimensional meteorological characteristics and power sequence is calculated by grey correlation analysis and sorted and layered. The first principal component of each layered characteristic variable is extracted by principal component analysis to achieve dimensionality reduction of high-dimensional meteorological characteristics. Finally, the COOT algorithm is introduced to optimize the hyperparameters of the gated recurrent unit prediction model, accelerate the model convergence speed, and improve the prediction accuracy of the model. The measured data of a wind farm in Guizhou are simulated and analyzed. The results show that compared with the prediction results of the traditional GRU model, the root mean square error, mean absolute error, and mean absolute percentage error of the proposed method are reduced 67.41%、72.25%、45.69%, and the prediction accuracy is higher than that of the other four combined prediction models, which effectively improves the prediction accuracy of ultra-short-term wind power.

Multi-objective grey correlation analysis based on CFRP Helical Milling simulation model

Multi-objective grey correlation analysis based on CFRP Helical Milling simulation model

Whether higher risk indicates severe loss in the flood disaster assessment: A comparative analysis in the Hubei province of central China

Study regionHubei province, Yangtze River Basin, Central China Study focusRisk and loss analysis constitutes a critical element of flood disaster management. Nevertheless, the relationship between risk and loss has been infrequently examined in the literature. Here we developed a comparative analysis framework for assessing flood risk and loss in Hubei Province. The risk model incorporates 22 indicators in terms of hazard, exposure, vulnerability and emergency response & recovery capability. Indicator weights were determined through a combination of objective and subjective weighting methods based on the game theory. Flood risk and loss levels were classified using fuzzy comprehensive evaluation and grey correlation analysis respectively. New hydrological insightsAnnual risk and loss maps exhibit a spatial pattern of higher levels in the eastern regions and lower levels in the western regions. However, the relationship between risk and loss was not as well as expected during designated flood periods. While regions impacted by disasters typically demonstrated higher risk levels, the risk in the regions unaffected by flood disasters appeared to be overestimated. By analyzing flood risk and loss across various temporal scales, this research contributes a novel perspective for the evaluation of flood risk models.

Capacity analysis of short-distance continuous diversion areas on mountainous urban expressways.

The short-distance continuous diversion area plays a crucial role within mountainous urban expressway systems, significantly enhancing the efficiency of specialized road sections through capacity analysis. This study develops a capacity calculation model tailored to the diversion area's unique characteristics and principal capacity-influencing factors. Initially, the research focuses on a specific short-distance continuous diversion area of a mountainous urban expressway, employing video trajectory tracking technology to gather trajectory data. This data serves as the basis for analyzing road and traffic characteristics. Subsequently, the model computes the capacity influenced by eight variables, including diversion point spacing and deceleration lane length, using VISSIM simulation experiments. A gray correlation analysis identifies key factors, which guide the establishment of the model's fundamental structure through two-factor surface fitting results. Mathematical statistical methods are then applied to resolve the model's parameters, culminating in a robust capacity calculation model. The findings reveal that diversion point spacing, along with primary and secondary diversion ratios, significantly influence capacity. Notably, the capacity exhibits a marked quadratic polynomial relationship with the primary diversion ratio and diversion point spacing, and a linear relationship with the secondary diversion ratio. The model's validity is confirmed through a case study at the diversion area north of Huacun Interchange in Chongqing Municipality, where the discrepancy between calculated and actual capacities is under 5%, underscoring the model's high accuracy. These results offer valuable theoretical and methodological support for the planning, design, and traffic management of diversion areas.

Multi-Objective Optimization of the Forming Process Parameters of Disc Forgings Based on Grey Correlation Analysis and the Response Surface Method

This paper introduces a multi-objective optimization problem (MPO) for the forming process parameters of disc forgings using grey relational analysis (GRA) and the response surface methodology (RSM). Firstly, an experimental design based on the Box–Behnken design (BBD) principle was established, and simulations were performed in Deform to obtain response data. Secondly, GRA was used to transform the MPO into a grey relational degree (GRD) problem, and the entropic weight method was integrated to ascertain the influence weights of each variable on GRD. Then, a quadratic polynomial prediction model based on the RSM was constructed, and its accuracy was ensured through model validation. Finally, the optimal process parameter combination was determined through the particle swarm optimization algorithm, which included a friction coefficient of 0.3, an initial temperature of 1250 °C, and a downward pressing speed of 7.5 mm/s. The results of the experimental investigation indicate that optimized process parameters significantly reduce the forming load, equivalent stress, and damage value, effectively enhancing the overall quality of forged parts.

Degradation mechanism and strength prediction of aeolian sand concrete under sulphate dry-wet cycles

In this paper, aeolian sand (AS) with different contents (0 %, 25 %, 50 %, 75 % and 100 %) was used as fine aggregate to prepare aeolian sand concrete (ASC). The effects of AS content and dry-wet cycle (DWC) times on the durability of ASC under sulfate (5 % Na2SO4) erosion conditions were investigated by DWC tests. The mass loss rate, compressive strength loss rate and relative dynamic elastic modulus (RDEM) were used as the macroscopic performance evaluation indexes, while the damage degradation mechanism of ASC was revealed by combining the microscopic technical means such as SEM, XRD, TG-DSC and NMR. The results show that the macroscopic properties of ASC under the action of DWC of sulphate all show the first increase and then decrease, as when the dosage of AS is below 50 %, the "bead effect" and "padding effect" of AS can further improve the internal densification of ASC, thus effectively resisting external sulphate erosion. During sulphate erosion, SO42- firstly reacts with cement hydration product Ca(OH)2 to generate erosion products such as Ettringite (AFt) and fills them within the original defects, with short-term rnhancement of macroscopic properties. As the DWC continue, the excessive erosion products accumulated, resulting in the destruction of pore structure and extension through the phenomenon, the matrix compactness is reduced, and the macroscopic properties degraded. The grey entropy correlation analysis yielded that the grey entropy correlation grade of bound fluid saturation, harmless pore percentage and less harmful pore percentage with compressive strength were all above 0.8, and the GM(1,4) strength prediction model established on the basis of the above pore structure parameters has a high prediction accuracy, and the relative errors between the predicted strength values and the actual strength values are within 10 %, and the research results can provide certain theoretical support for the study of the durability of ASC in sulfate erosion environment.

The Influence of the Sports Events Industry on Sichuan's Economic Growth

The sports industry occupies an important position in China's national economy, and the sports event industry is its core industry, and its role in regional economic development has received more and more attention from all parties. This paper takes Sichuan Province as an example to discuss the role of sports events in regional development. Firstly, it is a theoretical overview. This paper explores the mechanism of its economic effect from four perspectives: economic growth, industrial structure, regional agglomeration and city brand. Second is the case study. Through the grey correlation analysis of the relationship between sports and tourism industry, using the exponential smoothing method and ARMA method, and establishing a multi-indicator model, it is concluded that sports and tourism industry have the highest correlation and play a positive role in promoting regional development.

Prediction of Floor Failure Depth Based on Dividing Deep and Shallow Mining for Risk Assessment of Mine Water Inrush

Understanding and predicting floor failure depth is crucial for both mitigating mine water inrush hazards and safeguarding groundwater resources. Mining activities can significantly disturb the geological strata, leading to shifts and damage that may result in floor cracks. These disruptions can extend to confined aquifers, thereby increasing the risk of water inrushes. Such events not only pose a threat to the safety of mining operations but also jeopardize the sustainability of surrounding groundwater systems. Therefore, accurately predicting floor failure depth to take effective coal seam floor management measures is the key to reducing the impact of coal seam mining on water resources. Seventy-eight sets of data on coal seam floor failure depth in China were collected, and the main controlling factors were considered: mining depth (D1), working face inclination length (D2), coal seam inclination (D3), and mining thickness (D4). Firstly, the distance evaluation function based on Euclidean distance was constructed as the clustering effectiveness index, and the optimal cluster number K = 3 was determined. The collected data were clustered into three categories using the K-means clustering algorithm. It was found that the clustering results were positively correlated with the size of D1, indicating that D1 played a dominant role in the clustering. The D1 dividing points of the three types of samples were between 407.7~414.9 m and 750~900 m. On this basis, the grey correlation analysis method was used to analyze the order of the influence weights of the main controlling factors of coal seam floor failure depth. For the first group, the order was D2 > D1 > D3 > D4, while, in the other two, it was D1 > D2 > D3 > D4. D1 emerged as the most influential factor, surpassing D2. Therefore, D1 between 407.7 and 414.9 m could be used as the boundary, the first group could be classified as shallow mining, and the second and third groups could be classified as deep mining. Based on this boundary, CatBoost prediction models for the depth of coal seam floor failure in deep and shallow parts were constructed and the prediction results of the model test set were compared with the calculation results of the empirical formula. These models exhibited superior accuracy with a lower mean squared error (MSE) and mean absolute error (MAE) and a higher R-squared (R2) compared to the empirical formula. This study helps to enhance the understanding of coal seam floor behavior, guide floor management, and protect groundwater resources by defining deep and shallow mining to accurately predict floor failure depth.

Real-time prediction of metacentric height of ro-ro passenger ships in Qiongzhou strait based on improved RBF neural network

Addressing the complexities and real-time challenges in calculating ship metacentric height (GM), this study proposes an improved method using an optimized radial basis function neural network (RBFNN) for real-time GM prediction. Bayesian optimization is introduced to fine-tune the hyperparameters of the RBFNN, aiming to enhance the model's generalization performance. The study focuses on the Qiongzhou Strait Ro-ro passenger ship ‘Zijing No.11’ and selects three GM-related factors as neural network inputs using grey correlation analysis. The GM calculated by the empirical formula serves as the expected value, which is compared with predictions from various algorithms. Simulation results demonstrate that the improved RBFNN achieves significantly lower prediction errors compared to the unoptimized version. Furthermore, compared to other machine learning models and artificial neural networks, the proposed model exhibits superior performance in predicting ship initial stability height. Consequently, this model offers a practical tool for accurate and real-time GM prediction, enhancing intelligent stowage and operational efficiency in shipping.

Inhibitory mechanism on tyrosinase activity of flavonoids from flower buds of Sophora japonica L

The flower buds of Sophora japonica L. (FBSJ) have long been applied as Traditional Chinese Medicine (TCM) and functional food in East Asia. In this study, extracts of FBSJ from 11 different locations were analyzed using the HPLC method to establish their HPLC fingerprints. By determining the IC50 on tyrosinase activity, it was discovered that the extract from Kunming, Yunnan Province exhibited the strongest inhibitory activity. Further analysis, including partial least squares regression coefficient analysis and grey correlation analysis, regarded kaempferol, isorhamnetin, and quercetin as the compounds with significant tyrosinase inhibitory activities. To understand the inhibition mechanism of tyrosinase activity, various analytical techniques such as enzymatic kinetic analysis, fluorescence quenching, circular dichroism (CD), molecular docking, and molecular dynamics simulation were employed. The results revealed that quercetin, isorhamnetin, and kaempferol exhibited higher inhibitory activity and binding energy compared with kojic acid, indicating their potential value as natural tyrosinase inhibitors. This research provides a solid theoretical foundation for studying the application and mechanism of flavonoids against tyrosinase in FBSJ.

The mechanical properties of concrete exposed to harsh and complex environments of plateaus at early ages

The independently designed walk-in concrete low-pressure forming chamber and complex environment simulation chamber were employed to more accurately investigate the evolution of mechanical properties of concrete under the complex environment of the plateau. The quantitative comparison of the differences in the impact of each environmental factor on performance under complex coupled environments was conducted using two methods: grey correlation analysis and relative strength method. Meanwhile, the hydration and pore structure of concrete under the complex environment of plateau were studied by TG analysis and MIP analysis. The results showed that the high-altitude complex environment has a significant deterioration effect on the mechanical properties of concrete, mainly due to the decrease in the degree of hydration and pore structure deterioration. The environmental humidity and temperature difference are the main factors affecting the mechanical properties, and the complex environment has a more significant effect on the flexural strength of concrete than the compressive strength of concrete.

A novel framework for uncovering the coordinative spectrum-effect correlation of the effective components of Yangyin Tongnao Granules on cerebral ischemia-reperfusion injury in rats

Ethnopharmacological relevanceIschemic stroke is currently a major public health hazard.Yangyin Tongnao Granules (YYTN), a traditional Chinese medicinal prescription, exerts potential therapeutic effects on subsequent cerebral ischemia-reperfusion injury (CIRI) after ischemic stroke. However, further studies are required to comprehend the underlying mechanism of YYTN for treating CIRI and the associated spectrum-effect mechanisms. Aim of the studyTo investigate the coordinated correlation between the fingerprint and the pharmacodynamic indexes of the effective components (total flavonoids, total saponins, total alkaloids, and total phenolic acids) in YYTN for treating CIRI in rats. MethodsThe fingerprints of five specific components (ligustrazine, puerarin, ferulic acid, calycosin, and formononetin) of YYTN in rats with middle cerebral artery occlusion (MCAO) were established using high-performance liquid chromatography (HPLC), and their peak areas were quantified in plasma samples. The pharmacodynamic indexes of tumor necrosis factor-alpha (TNF-α), cytochrome c (Cyt-C), and total superoxide dismutase (T-SOD) were integrated using the Criteria Importance Through Intercriteria Correlation (CRITIC) method to create a comprehensive evaluation index. Spectrum-effect correlation was analyzed by performing gray relation analysis (GRA), correlation analysis (CA), and partial least squares regression (PLSR). The Borda method was then applied to integrate the obtained results. ResultsIn MCAO rats, the effective components of YYTN reduced TNF-α and Cyt-C and increased T-SOD, which indicates their anti-inflammatory, antiapoptotic, and antioxidant effects. Spectrum-effect CA revealed certain associations between the chromatographic peaks of the five main components and the comprehensive pharmacodynamic evaluation index. Of these components, formononetin displayed the highest correlation, whereas ferulic acid exhibited the lowest correlation. All components showed a positive correlation. Using the Borda method, the components were ranked as follows based on correlation: formononetin > calycosin > ligustrazine > puerarin > ferulic acid. ConclusionsThe effective components of YYTN exhibited synergistic effects in the treatment of MCAO rats, which could potentially be attributed to their multitarget and multipathway mechanisms. The Borda method-based spectrum-effect correlation analysis provides a coordinated approach to investigate the relationship between fingerprint and pharmacodynamics of traditional Chinese medicine (TCM).