Grey Correlation Analysis Method Research Articles

Study on the Operation Safety of Sea Sightseeing Tourist Ships in the Waters of Kowloon Bay, Weihai

With the rapid development of social economy, tourism as a tertiary industry has developed rapidly, and sea sightseeing has become a popular project in coastal areas. These areas not only meet the requirements of tourists, but also promote the rapid development of the regional economy and make a great contribution to the development of local tourism. Tourist ship operation is one of the important ways for people to enjoy the scenery of the sea and experience boat travel, but also faces many problems such as navigation safety. In recent years, tourism and aviation safety incidents at home and abroad have frequently attracted social attention, and strengthening tourism navigation safety supervision has become a top priority. This paper selects the operation safety of maritime sightseeing and tourist vessels in the waters of Weihai Jiulong Bay as the research object, starts from the analysis of the factors affecting the operation safety of sightseeing and tourism vessels in Kowloon Bay, and establishes a hierarchical model of the operational safety factors of tourist vessels in Weihai Jiulong Bay from the perspective of the "man-ship-environment-management" system. The grey correlation analysis method is used to study the risk factors affecting the operation safety of tourist ships, and corresponding improvement measures are proposed to improve the safety of maritime sightseeing tourism and the safety of tourists.

A vulnerability evaluation method of earthen sites based on entropy weight-TOPSIS and K-means clustering

The degradation of earthen sites due to natural and human factors has become a pressing issue, necessitating urgent protection measures. In this context, accurate assessment of the vulnerability of earthen sites is essential for the development of effective conservation strategies. In this study, a comprehensive evaluation framework that incorporates multiple indicators is proposed. In particular, the entropy weight- (Technique for Order Preference by Similarity to an Ideal Solution) TOPSIS method is employed for quantitative vulnerability assessment and combined with K-means clustering to define vulnerability levels for earthen sites. To validate the proposed approach, the vulnerability of 29 sections of the Ming Great Wall is evaluated. Eventually, the 29 earthen sites are categorized into three levels: high, medium, and low, according to their degree of vulnerability. The results of gray correlation analysis and entropy weight-TOPSIS method are compared using the ontology missing amount in the original data as the validation standard. The results show that the Pearson correlation coefficient value of the entropy weight-TOPSIS method with the ontology missing amount was 0.859, while the Pearson correlation coefficient value of the gray correlation analysis method with the ontology missing amount was 0.691, so that the results of the entropy weight-TOPSIS method can more accurately reflect the actual vulnerability of earthen sites.

Optimizing the performance of TPCB/SCA composite-modified asphalt using improved response surface methodology

Abstract A composite-modified asphalt was developed by incorporating tire pyrolytic carbon black (TPCB) with a silane coupling agent (SCA) to enhance its ductility and storage stability. The functional binding between asphalt and TPCB was improved by the addition of SCA. The gray correlation comprehensive evaluation method is incorporated into the response surface methodology (RSM), leading to an improved RSM. The improved RSM was employed to optimize the content of the modifier and the preparation process to enhance overall performance. A central composite design-based experiment was conducted to optimize the penetration, softening point, 10°C ductility, Brookfield rotational viscosity, and storage stability indicators of modified asphalt. The response surface of the gray comprehensive evaluation value of the evaluation indicators was calculated using the gray correlation analysis method, and a second-order regression model was established between independent variables such as TPCB, SCA content, and shear time factor and the gray comprehensive evaluation value. This model analyzed the impact of a single variable and variable interaction on the performance of the TPCB/SCA composite-modified asphalt. The optimized model results showed that the preparation parameters that optimize the expected comprehensive performance of the composite-modified asphalt are 9.2% TPCB content, 2.1% SCA content, and a shear time of 56.3 min. Finally, the TPCB/SCA composite-modified asphalt prepared with the improved RSM exhibited the highest gray comprehensive evaluation value and the best overall performance, indicating the feasibility of the optimized preparation parameters with the improved RSM.

Bandgap characteristic and bandgap expansion of a petal-shaped metamaterial

The control of low frequency vibration and noise is an urgent problem. The bandgap characteristic of metamaterials is the key to solve this problem. In this paper, a plum metamaterial structure is designed based on the local resonance theory and its bandgap characteristics are studied and extended. The structure is calculated by finite element method, and its vibration modal characteristics are analyzed. The corresponding spring oscillator equivalent model is established and verified. Plum metamaterial structure has a wide band gap in the low frequency range below 250Hz. The band gap width is about 177Hz, and its frequency response function calculation results show that it has good attenuation effect. By changing the material and size parameters of the structure, the low frequency band gap can be adjusted to meet the requirements of practical applications. The influence priority of each parameter is determined by grey correlation analysis method. A phonon-like crystal model is proposed, and the structural design and research results provide a theoretical basis and an effective method for obtaining the low frequency band gap in the study of metamaterials, and have a potential application prospect in the low frequency vibration noise reduction.

Performance Analysis of Universities Based on Combination Weighting Method and Grey Correlation Analysis

The performance evaluation of universities is of great significance for improving their educational level and allocating funding resources. This article constructs a performance evaluation model for universities based on the combination weighting method and grey correlation analysis. The model first uses principal component analysis and average mutual information method to select indicator features and select indicators with high importance; On this basis, the grey correlation analysis method is used to obtain the relationship between input indicators and output indicators; Finally, develop a visual performance analysis platform for universities using Python language and validate it with examples to conduct research. The research results indicate that the model and platform can effectively and intuitively display evaluation results, and can assist education management departments in identifying shortcomings and formulating targeted improvement strategies based on evaluation results.

Performance Test, Index System Establishment, and Comprehensive Evaluation of Earthquake Rescue Robots

To effectively enhance the adaptability of earthquake rescue robots in dynamic environments and complex tasks, there is an urgent need for a comprehensive evaluation method that encompasses establishing an evaluation index system, testing performance indexes, and conducting performance evaluation. Firstly, four main criterion and twenty-three sub-criterion indexes are established by conducting a comprehensive review of existing assessment measures for rescue robots across diverse domains. These indexes are validated through test modules developed by the National Earthquake Response Support Service to obtain corresponding values for each criterion. Moreover, a method for establishing the index system is proposed based on the fuzzy clustering analysis and grey correlation analysis methods. This method effectively addresses issues related to excessive subjectivity, redundancy, and ambiguous stratification of indexes. Subsequently, the DEMATEL is employed to scrutinize the interrelationships and causal connections among each index within the established index system, leading to the identification of input and output indexes based on the analysis outcomes. Finally, as an empirical example, three earthquake rescue robots are comprehensively evaluated and ranked using the super efficiency DEA model. Alongside analyzing results regarding input redundancy and output deficiency, targeted improvement suggestions are provided for each earthquake rescue robot. Additionally, comparison analysis with the entropy weight method and VIKOR method verifies the effectiveness of our proposed method.

Analysis of the influence of karst cave parameters on surface settlement in TBM tunnelling

In order to study the sensitivity of multiple karst cave factors on surface settlement during Tunnel Boring Machine(referred to TBM hereinafter) tunnelling, a three-dimensional numerical model is built by taking a subway project as an example and combining MIDAS GTS NX finite element software. Secondly, the influence of the radius, height, angle, vertical net distance, and horizontal distance of the karst cave on the maximum surface settlement is studied and sorted under the two working conditions of treatment and untreated using the grey correlation analysis method. Additionally, a multi-factor numerical model of the untreated karst cave is established. Finally, based on the preceding research, a multi-factor prediction model for the maximum surface settlement is proposed and tested. The results reveal that when the karst cave is not treated, the radius and height of the karst cave have a significant effect on the maximum surface settlement. After the cave treatment, the influence of the cave parameters on the maximum settlement of the surface is greatly reduced. The calculating modelcreated in this study offers excellent prediction accuracy and good adaptability.

Research on multi-UAV collaborative electronic countermeasures effectiveness method based on CRITIC weighting and improved gray correlation analysis

Multi-UAV cluster technology is a hot topic in modern electronic countermeasures research. Based on the “OODA loop” theory of electronic countermeasures, this paper analyzes the effectiveness evaluation method of multi-UAV collaborative electronic countermeasures. We establish an electronic countermeasures correlation state analysis model based on CRITIC weighting and improved gray correlation theory. This method combines multi-UAV collaborative scene examples and use the gray state correlation analysis method based on the dynamic resolution coefficient. We simulate the effects of electronic countermeasures and various influencing factors on the expected task objectives and verify the effectiveness of the proposed method. The results show that this method can better adapt to the dynamic electronic countermeasures scenarios of multi-UAV clusters and has certain participation value for comprehensively and systematically improving the effectiveness evaluation of electronic countermeasures.

Analysis of Factors Affecting Carbon Emissions based on Gray Correlation Analysis

In order to explore the influencing factors of carbon dioxide emissions, this paper collects data on carbon emissions and several influencing factors that may be related to its changes from 2004 to 2021, considering that too many indicators may make the data redundant and lack of representativeness, using the K-Means clustering algorithm to classify the indicators and defining the names of the corresponding first-level indicators, and analyzing the elbow diagrams for the determination of the model K-value. For the determination of the K value of the model, the optimal number of clusters was analyzed using the elbow diagram, so that the center of each cluster as the first-level indicator data was spliced with the normalized emission data to form a new dataset, and the correlation coefficients between the first-level indicators and the carbon emissions were finally calculated using the grey correlation analysis method. The results show that the ability to mitigate carbon dioxide content has the greatest impact on carbon content, and the correlation coefficient between the two reaches 0.756, which indicates that increasing the green area is very effective in achieving the goal of energy saving and emission reduction.

Spatial Pattern of Ecosystem Services and the Mechanism of Eco-Industry Formation in South China Karst Nature Reserves

Karst nature reserve (NR) ecosystems are vulnerable, and the development of regulatory and cultural services industries is still in its infancy. Realization of ecological product value (EPV) is a crucial way to promote the integration of eco-protection and industrial development in nature reserves (NRs). This study calculates EPV using a modified equivalent factor, analyzes the spatial pattern of EPV using the fishnet tool in Arc GIS, and constructs a model for realizing EPV. Finally, the driving factors for the formation of eco-industry are identified using the grey correlation analysis (GCA) method. The results show that (1) the regulatory service products in karst NRs play a decisive role in EPV, and forest ecosystems have significant EPV potential; (2) high-value grids are concentrated in the core and buffer zones of karst NRs and the spatial distribution of EPV in the experimental zone is highly heterogeneous, with high and low-value grids in mixed distribution; (3) the realization model of EPV in karst NRs follows the logic of “preservation, transformation, and appreciation”; (4) human resources (0.813), ecology (0.798), industry (0.693), policy (0.783), the market (0.778), and economy (0.715) are essential drivers for the formation of eco-industry in karst NRs. Overall, karst NRs can promote the realization of EPV through planning and regulation of land use, based on the interaction between internal and external factors, to promote the coordinated development of eco-industry in karst NRs. This study provides a reference for the scientific management of eco-resources and the sustainable development of eco-industry in karst NRs.

Carbon emission prediction of construction industry in Sichuan Province based on the GA-BP model.

The reduction of the carbon emissions of construction industry is urgent. Therefore, it is essential to accurately predict the carbon emissions of the provincial construction industry, which can support differentiation emission reduction policies in China. This paper proposes a carbon emission prediction model that optimizes the backpropagation (BP) neural network by genetic algorithm (GA) to predict carbon emission of construction industry, or "GA-BP". To begin with, the carbon emissions of construction industry in Sichuan Province from 2000 to 2020 are calculated by the emission factor method. Further, the electricity correction factor is introduced to eliminate the regional difference in electricity carbon emission coefficient. Finally, four factors are selected by the grey correlation analysis method to predict the carbon emission of construction industry in Sichuan Province from 2021 to 2025. The results show that the carbon emissions of construction industry in Sichuan Province have been trending up in the past two decades, with an average increase rate of 10.51%. The GA-BP model is a high-precision prediction model to predict carbon emissions of construction industry. The mean absolute percentage error (MAPE) of the model is only 6.303%, and its coefficient of determination is 0.853. Moreover, the carbon emissions of construction industry in Sichuan Province will reach 8891.97 million tons of CO2 in 2025. The GA-BP model can effectively predict the future carbon emissions of construction industry in Sichuan Province, which provides a new idea for the green and sustainable development of construction industry in Sichuan Province.

Multi-Objective Optimization of Low-Alloy Hot-Rolled Strip Cooling Process Based on Gray Correlation Analysis

The residual stress in low-alloy hot-rolled strips seriously affects the use and processing of products. Reducing residual stress is important for improving the product quality of hot-rolled strips. In this paper, the changes in grain size and residual stress of hot-rolled strips under different cooling processes were investigated via thermal simulation experiments and electron backscatter diffraction. It was found that the optimum cooling process solution for single-objective optimization of grain size was a final rolling temperature of 875 °C, a laminar cooling speed of 50 °C/s, and a coiling temperature of 550 °C. When single-objective optimization of residual stress was carried out, the optimal cooling process scheme was 900 °C for final rolling temperature, 20 °C/s for laminar cooling speed, and 625 °C for coiling temperature. The significance of the effect of cooling processes on grain size and residual stress was analyzed based on the extreme deviation of the effect of each cooling process on grain size and residual stress in orthogonal experiments. The results show that the coiling temperature was the most influential factor on grain size and residual stress among the cooling process parameters. The difference was that grain size increased with increasing coiling temperature, and residual stress decreased with increasing coiling temperature. Using both grain size and residual stress as evaluation indicators, a multi-objective optimization of the cooling process for hot-rolled strips was carried out via the gray correlation analysis method. The optimized solution was 875 °C final rolling temperature, 30 °C/s laminar cooling speed, and 625 °C coiling temperature. At this time, the grain size was 4.8 μm, and the KAM (Kernel Average Misorientation) was 0.40°. The grain size under the actual production process scheme was 4.4 μm with a KAM of 0.78°. Compared to the actual production process solution, the multi-objective optimization solution showed little change in grain size, with only a 9% increase and a 49% reduction in KAM. The optimization scheme in this paper could significantly reduce the level of residual stresses while ensuring the fine grain size of hot-rolled strips, thus improving the overall quality of hot-rolled strips.

Comprehensive Assessment and Empirical Research on Green and Low-Carbon Technologies in the Steel Industry

The iron and steel industry is the leading industry supporting China’s industrial sector. Currently, there is less assessment work on green and low-carbon technologies for the iron and steel industry. This study clarifies the overall strategy of technology assessment by researching the relevant theories and methods of technology assessment. The study further establishes a scientific and reasonable comprehensive assessment index system of green and low-carbon technologies for the iron and steel industry from the aspects of technology index, economy and promotion, and application, including factors such as 11 indexes, the amount of energy saving, carbon dioxide emission reduction, and the resource recovery rate by utilising analytical and comprehensive methods and combining with the characteristics of the technologies. By analysing and comparing the advantages and disadvantages of the commonly used assessment methods, the entropy weighting method, grey correlation analysis method, and TOPSIS (technique for order preference by similarity to an ideal solution) method are combined and optimised to construct a comprehensive assessment model. The Latin hypercube sampling method is also introduced to analyse the technical parameters in combination with the evaluation model. Finally, fourteen iron and steel green and low-carbon technologies were selected for case assessment and uncertainty analysis of technical parameters, and it was found that the comprehensive assessment result of gas combined cycle power generation technology was optimal. After determining the weights of each assessment indicator through the entropy weighting method, it is concluded that the technical performance indicator > economic indicator > promotional indicator. A comparative analysis of the results under the three preference decisions concludes that technical performance is the main obstacle to improving the comprehensive assessment score of the technology, followed by the economics of the technology. Finally, the uncertainty analysis of the technical parameters shows that the fluctuation of the technical parameters not only affects the performance of the technology, but also affects the weights of the indicators and the comprehensive evaluation results of the technology.

The location analysis and efficient control of hidden coal spontaneous combustion disaster in coal mine goaf: A case study

Coal spontaneous combustion significantly threatens the mine production safety. This paper focuses on the practical aspects of the disaster within the sealed goaf of Pingmei No. 11 mine. Obtained the characteristic parameters of spontaneous combustion in goaf by arranging high-level drilling field and drilling method. The grey correlation analysis method was applied to analyze the determination index of the effective characterization of the hidden spontaneous combustion area range, and interpolation aided in assessing these indicators before and after the increase amount of N2 injection. All showed that the hidden spontaneous combustion area was determined to be 70–80 m away from the return air side and 10–15 m away from the stop line, and the comprehensive treatment technologies are executed to control the spontaneous combustion hazards, including injecting inert gas to cool the high-temperature area, injecting the aqueous foam to cover the fire source, and plugging leakage to isolation the O2. Finally, the O2 concentration in goaf dropped below 5.0%, and carbon monoxide concentration fell below 0.001% after implementing these methods, effectively controlling the coal spontaneous combustion disaster. The successful management of concealed coal spontaneous combustion disasters offers a valuable reference for identifying and efficiently addressing such incidents in goaf areas.

Optimization of drilling parameters for coal seam gas extraction considering fluid–solid coupling and field application

AbstractAffect gas extraction efficiency to find out the optimum well location parameters, based on the gray correlation analysis of borehole diameter, borehole spacing, and extraction pressure three boreholes parameters that influence efficiency of gas extraction from the design of orthogonal experiment, using COMSOL simulate the effective radius of extraction under different experiments, and the effective radius of extraction for optimizing index quantitative gas extraction efficiency. The results showed that: factors affecting the gas extraction efficiency of the correlation between high and low aperture drilling, borehole spacing, and extraction from extraction negative pressure, it is concluded that the influence parameters of optimal layout parameter values, respectively, borehole diameter 8 cm and 3 m borehole spacing, extraction pressure 50 kPa, combined with the numerical simulation analysis using the optimal layout of gas drilling extraction from about 30 days. The decrease in gas pressure is about 45%, which basically meets the extraction standard, and the decreasing trend of gas pressure is obviously slowed down when the extraction time is longer than 30 days. The engineering experiment is carried out in the 9306 transport lane of a mine in Guizhou Province, and the results are basically consistent with the simulation results, which verify the rationality of the gray correlation analysis method to optimize the drilling parameters, and provide a theoretical basis for the optimization of drilling parameters.

Fault Section Localization Method for Distribution Network Based on Synchronous Phasor Measurement

Background: The accurate locating of fault sections in a distribution network can lay an effective foundation for the rapid processing of faults. However, the waveform of highresistance grounding faults is relatively weak, which increases the difficulty of fault feature extraction and localization. In addition, the complex operating conditions and interference factors of the actual distribution network can affect the fault section localization method, leading to incorrect location problems. background: The accurate locating of fault sections in distribution network can lay an effective foundation for rapid processing of faults. However, the waveform of high resistance grounding faults is relatively weak, which increases the difficulty of fault feature extraction and localization. In addition, the complex operating conditions and interference factors of the actual distribution network can affect the fault section localization method, leading to incorrect location problems. Objective: In order to overcome the limitations of existing fault section localization methods on fault resistance values and application scenarios, a fault section localization method for distribution networks based on synchronous phasor measurement is proposed in this paper. objective: In order to overcome the limitations of existing fault section localization methods on fault resistance values and application scenarios, a fault section localization method for distribution network based on synchronous phasor measurement is proposed in this paper. Methods: Firstly, the transient zero sequence equivalent network of single-phase to ground faults in the distribution network is analyzed, revealing the differences in zero-sequence current within different sections of the faulty line. At the same time, based on the zero-sequence current waveform recorded by the waveform measurement device in actual distribution network, the characteristics of the waveform in different sections in the time and frequency domains are analyzed. Furthermore, a fault feature extraction method based on wavelet packet transform is proposed to construct fault differential features for different sections. Then, the grey correlation analysis method is adopted to calculate the correlation coefficients between different sections to construct locating criteria, thereby achieving accurate locating of fault sections in distribution network. method: Firstly, the transient zero sequence equivalent network of single-phase to ground faults in the distribution network is analyzed, revealing the differences in zero-sequence current within different sections of the faulty line. At the same time, based on the zero-sequence current waveform recorded by the waveform measurement device in actual distribution network, the characteristics of the waveform in different sections in the time and frequency domains are analyzed. Furthermore, a fault feature extraction method based on wavelet packet transform is proposed to construct fault differential features for different sections. Then, the grey correlation analysis method is adopted to calculate the correlation coefficients between different sections to construct locating criteria, thereby achieving accurate locating of fault sections in distribution network. Results: The experimental results using field data indicate that the localization accuracy can reach 98.90%, and the calculation time is about 102.65ms, which has high localization accuracy and localization efficiency. result: The experimental results using field data indicate that the proposed method has high localization accuracy and efficiency. Conclusion: Through analysis and relevant experiments, it is concluded that the proposed method can accurately locate faults in actual distribution networks, and still has correct locating results for high resistance grounding faults. The effectiveness of the method has been verified.

Analysis of Japanese Translation Skills Based on the Perspective of Multimedia Cultural Differences

Abstract This paper screens and calculates the factors affecting the quality of Japanese translation through the gray correlation analysis method. First, the Pearson correlation coefficient is utilized to explore the correlation between each factor and translation quality, and the multicollinearity between the influencing factors is tested. A quadratic test was conducted on the influencing factors using Lasso variable selection and ridge regression methods to eliminate those with linear correlation. On this basis, Japanese translation skills are designed and practiced from the perspectives of naturalized and alienated translation strategies to address cultural differences. The correlation coefficients of the factors affecting the quality of Japanese translation ranged from 0.7017 to 0.9309. The correlation coefficient between translation integrity and average sentence length was 0.491. The overall rating of the translated texts of each student reached a maximum of 97.87 points after using the translation technique. The translation technique in this paper is more effective in Japanese translation, which provides a reference method for the translation strategy under the perspective of cultural differences between China and Japan, and also helps to effectively convey the country’s culture.

Interdisciplinary Talent Cultivation and Development of Drama, Film and Television Literature in the Perspective of New Media

Abstract With the change in knowledge production mode, “inter-specialization of drama, film and literature” has become an important cradle of innovation. In this paper, under the perspective of new media, we have constructed an interdisciplinary talent cultivation mode of drama, film, and literature and its quality evaluation index system, and after standardizing the indexes by using the extreme value method, we calculate the index weights of the inter-disciplinary talent cultivation quality evaluation system by using the entropy weight method. Combining the indicators obtained at all levels and the gray correlation analysis method, the quality level of interprofessional talent training in drama, film, and literature is comprehensively evaluated. To further explore the effectiveness of inter-specialty talent cultivation in drama, film, and literature, a quantitative analysis is carried out with the drama, film, and literature major of T College of Arts as an example. The results show that: In the evaluation of talent cultivation quality, the weight values of ideological and moral level and relocatable ability are 0.342 and 0.207, and the overall proximity of the overall level of interprofessional talent cultivation of drama, film, and literature from 2018 to 2022 has been increased by 0.16. The enhancement of the quality of interprofessional talent cultivation of drama, film, and literature needs to break down the current professional barriers, coordinate the planning, share the resources, and collaborate in the cultivation of human beings to ensure that inter-professional education is steadily promoted and the quality of talent cultivation is effectively improved.

Research on the Integration Mode of Teaching Chinese Cultural Elements and English Translation Courses Based on the Integration Model

Abstract How to integrate Chinese cultural elements with English translation courses has been a major topic of discussion within English teaching. For this, this paper proposes to integrate traditional Chinese cultural elements into English translation courses, combining the entropy weighting method and the gray correlation analysis method to calculate the degree of integration and influencing factors of the two. It firstly eliminates the incomparability caused by different outlines and the positive and negative directions of the indicators through the dimensionless processing of the indicator values, and secondly uses the entropy weighting method to calculate the objective weights of the indicators, and applies TOPSIS to make a comprehensive evaluation. To assess the integration of Chinese cultural elements and English translation course teaching at this school, use gray correlation analysis. The practical application of designing English translation test papers with Chinese cultural elements and integrating traditional Chinese cultural elements into the teaching of English courses was carried out at a university. The correlation between article translation and the total score is the largest (0.728), and the correlation of basic translation ability is 0.658. The ones that have an impact on the translation ability of Chinese traditional elements are, in descending order, basic reading (0.8175), listening to English (0.7951), comprehensive ability (0.7422), and English writing (0.6384).

Integration of Instrumental Elements and Vocal Teaching Based on Music Core Literacy

Abstract The current lack of music core literacy in vocal music teaching needs to be solved, and this paper aims to improve this problem. In the paper, a hybrid attention module is added to the multi-channel of MFCC to extract the acoustic elements of the musical instruments, and after characterizing the musical instruments as a multi-view sequence, visual features and temporal features are fused, and a graph convolution module is added to extract the visual elements of the musical instruments, and the two are fused. After extracting the elements of musical instruments, the development of vocal fusion teaching of the two was analyzed by combining the gray correlation analysis method, and experiments were designed on the basis of which to investigate the extraction effect of the elements of musical instruments as well as the development of vocal fusion pedagogy. The results show that the average accuracy of instrumental elements of the multimodal extraction model is 0.919, which is improved by 0.17 compared with the Baseline classification accuracy, and the extraction accuracy can reach more than 90% for flute, percussion instrument, plucked instrument, wind instrument, suona, xiao, sheng, wind instrument, pipa, and erhu. The gray correlation of the fourth grade ranged from 0.75 to 0.88, with a high improvement in the same grade, and the gray correlation of different grades all ranged from 0.3 to 1.0, and the higher the grade, the better the development.