bluuebunny/crossref_metadata_2025 huggingface dataset:
Research on dynamic detection method of bridge vehicle load based on optimization algorithm
Authors: Wang Fang
Published: September 2023

In recent years, accidents causing casualties and losses to people and property have occurred frequently throughout the country due to bridge safety problems, causing huge losses to the country and people’s property. To prevent the recurrence of such incidents and effectively maintain the safety and interests of the people, this paper intends to use the optimization algorithm as the technical support to study the optimal method for dynamic detection of vehicle loads on bridges. The gradient descent method is used to obtain the deflection influence line of the bridge dynamic test structure and the overall vibration frequency of the structure. The bridge test area is then selected by the stochastic gradient descent method, and the measured strain and deflection influence lines are used to modify the initial finite element model of the bridge so that the finite element model can truly reflect the actual mechanical behavior of the bridge structure. According to the survey, as of the end of 2019, there were 878,300 highway bridges with a total mileage of 6063.46 m, which was 26,800 more than in 2018, and the mileage increased by 4,948,600 m. Among them, mega bridges accounted for 5716 bridges with a mileage of 10,323,300 m, and bridges accounted for 108,344 bridges with a mileage of 29,237,500 m. Many bridges in service provide convenience for people’s life and travel but also bring great challenges to bridge management and maintenance, bridge appraisal, and assessment. Monitoring the bridge load condition helps to grasp the actual working condition of bridges in a timely and accurate manner and to warn and repair the safety hazards that appear on bridges in time to prevent accidents.
Research on physical human-computer interaction virtual reality fitness method combined with Unity3D technology
Authors: Zhang Weihua
Published: September 2023

To respond to the slogan of the national fitness movement, improve the quality of the national fitness movement, and provide scientific reference to public fitness, this paper studies the fitness method of Unity3D technology and somatosensory human-computer interaction virtual reality technology. Firstly, we build a somatosensory HCI virtual fitness system with Unity3D and Kinect technology, verify the data with an edge detection operator, get the simulation results of the somatosensory HCI virtual reality fitness system, and then get the fitness method based on the somatosensory HCI virtual reality technology according to the results. The data show that the fitness industry is seeing new highs as the national fitness membership reaches 75.13 million people as of December 2021, while the growth of women among them increases from 13.5 million in 2017 to 55.6 million in 2021. Among the 800 fitness methods, the physical therapy and rehabilitation category accounts for 1/3, and fitness, bodybuilding and health care each account for about 1/5. The comfort zone of fitness differs between men and women, ranging from 0.6-1.2 for men and 0.5-0.9 for women. The research in this paper can provide reasonable fitness advice to the fitness population and promote the healthy development of the fitness industry.
A Study on Multiple Interactive Teaching Models of English in Universities under Information Technology Environment
Authors: Li Zhiqiang
Published: September 2023

After modern information technology with the computer network as the core has entered the practice of college English teaching, the traditional college English teaching mode has undergone many changes and has brought confusion and challenges to English teaching. To this end, this study addresses the current situation of the reform practice of English teaching in colleges and universities and applies the relevant theories of foreign language teaching to elaborate and justify the multiple interactive teaching modes of English in colleges and universities under the information technology environment. The LDA-WO model is constructed in this paper, and students’ performance in the selected experimental and control classes before and after the multi-interactive teaching is analyzed and studied. The results of the analysis showed that the Z-values of students’ independent learning in the experimental class were 2.67, 3.78, 4.25, 3.17, and 5.61, all < Z0.05 = 1.96, which means that the student’s independent learning in the experimental class had improved significantly after the experiment, and there was a significant difference compared with the control class. In conclusion, the multi-interactive teaching model has a certain improvement effect on college students’ English listening and speaking ability, literacy ability, and strategy useability.
Research on the design of mechanical robot control system for industrial PC in the context of big data
Authors: Chen Yalin
Published: September 2023

In the digitalization of big data information, how to use big data technology to design and study the mechanical robot control system of industrial PC has become a key topic of concern in today’s society. In this paper, robot kinematic modeling is mainly used to analyze and study the robot motion equations and control system operation mechanism, and the motion controller of the industrial robot control system is selected from the CLIPPERPMAC controller of the PMAC motion controller series. The approach to reducing the operation error of the industrial robot system from the control perspective is discussed. The error is reduced by adjusting the PID parameters of the PMAC motion controller in automatic and manual ways, and the error is further reduced by introducing fuzzy control algorithms. By comparing the original curve, the curve after the PID adjustment of PMAC itself and the curve after the introduction of the fuzzy controller, the curve error is kept below 5%, which is determined to be an effective method to reduce the error. This study can precisely realize the design and research of mechanical robot control systems, thus providing a guiding reference value for the research of industrial robot mechanization.
Research on the digital transformation path of banks in the era of big data
Authors: Xing Tong
Published: September 2023

This paper proposes a weighted large-scale data subspace clustering algorithm to enable it to adapt to the mega-customer environment for financial banks to respond quickly to customer data. Firstly, based on the K-means combined with a genetic algorithm, an improved method for the sensitivity problem of initial clustering center selection of K-means algorithm is proposed. By weighting the variables and streaming data batch processing method as a guide, the improvement method is proposed for the problem that the mean algorithm cannot identify the correct clustering center caused by the ultra-large-scale data environment, leading to the iteration number approaching infinity. The accuracy of the K-mean algorithm, the optimized initial clustering center algorithm, and the algorithm in this paper are 89.61%, 94.37% and 96.94%, respectively. In terms of running time, the highest running time of this algorithm is 10.96 seconds, which is faster than the running time of the other two algorithms. Finally, the financial analysis of the financial bank that completed the digital transformation with the help of the algorithm in this paper, the bank achieved a business of 150.832 billion yuan in 2021, an increase of 11% compared with the end of last year. Net profit achieved 44.883 billion yuan, an increase of 25.8% compared to the end of last year. Therefore, the algorithm in this paper has high advantages in terms of accuracy, efficiency, and practicality, proving that digital transformation can improve bank profits. It also provides a path and direction of transformation for various urban and agricultural commercial banks and other small credit unions.
Analysis of the Plea Leniency System and Plea Bargaining System in the Era of Big Data
Authors: Zhu Lehua
Published: September 2023

In the era of big data, comparing plea leniency and plea bargaining systems can bring important insights to legal practitioners. In this paper, by studying the principle of the fuzzy K-mean clustering method, optimization using rough set theory is proposed for the problem of unclear boundaries in the fuzzy clustering process. Then, based on comparing the origins and development of the plea-leniency system and the plea-bargain system, big data analysis of the plea-leniency system cases in China and the plea-bargain cases in the United States is conducted using the fuzzy clustering method based on rough sets. The application rate of China’s plea leniency system is, on average, 49.67% lower than that of the U.S. plea bargaining system. In terms of the sentencing range, the plea leniency system is 32.73% lower than the plea bargaining system. Compared to the two, the plea leniency system is more stringent in terms of discretionary limits and standards of proof. Based on the big data analysis, the plea leniency system should expand the application area and strict leniency standards and improve the relevant subject system and evidence disclosure system.
Sentiment analysis of domestic movie reviews based on a discrete regression model
Authors: Liu Jingting
Published: September 2023

In the context of the rapid development of big data information digitization, how to use big data technology to analyze the sentiment of domestic movie reviews is a hot topic of current concern. In this paper, we use two similarly themed Chinese movie reviews as the basis and use discrete regression models to study the emotional tendency of movie reviews. Firstly, the ROC curves of the regression model are plotted based on the convolutional neural network to construct the text classification task metrics and the logistic discrete regression algorithm. The prediction probability at the bottom of the curve is 56.3%, and the 95% confidence interval is [56%, 56.6%], indicating the model’s high accuracy. Then, the factors affecting effective tendency were analyzed by the logistic discrete regression model, and both user level (UL) and per capita disposable income (PCDI) had significant effects on affective tendency (ET) (both p-values were less than 0.001), and the coefficients of both influencing factors were less than 0. This indicates that user level (UL) and per capita disposable income (PCDI) have significant negative effects on affective tendency (ET) have a significant negative effect on affective tendency (ET), i.e., the higher the user level, the more likely it is to have a bad review, i.e., the higher the per capita disposable income, the more likely it is to have a bad review. This study provides a comprehensive and objective evaluation of domestic movie reviews and provides a guiding reference basis for the development direction and progress of Chinese movies.
Research on the integration development path of rural tourism and traditional culture protection and inheritance based on the integration of big data
Authors: Hu Bin , Mu Chunlin , Tao Ting
Published: September 2023

This paper studies the integration and development of rural tourism and cultural preservation and inheritance, aiming to explore new development paths for rural tourism. This paper first introduces the basic algorithm and steps of plain Bayesian, and the fusion improves the principal kernel components of the Bayesian model. Using the improved plain Bayesian model to analyze rural tourism and traditional culture protection and inheritance, the problems in the integration process are analyzed from the rural cultural tourism situation, the integration of rural tourism and cultural protection and inheritance, as well as the proposed integration development countermeasures and the construction of the integration development path. In the study of the integration situation, the single indicator of infrastructure construction under the development level system reaches 0.9578, ranking first in the ratio of all three indicators, indicating that infrastructure construction is the most important factor affecting tourism development. Policy support and the construction of the six elements of tourism ranked second at 0.453, indicating its importance. Regarding countermeasures, 90% believe that cultural heritage buildings should be protected, 95% believe that cultural connotations should be deeply explored, and 85% believe that the integration of culture and tourism should be strengthened. Integrating rural tourism and traditional culture preservation is a long-term process that requires continuous exploration and improvement.
Research on the integration and development of student management and ideological and political education in universities based on environmental psychology
Authors: Hao Shuxin
Published: September 2023

To cultivate college students to become new intellectuals with virtue and talent who master modern scientific and cultural knowledge and are physically healthy. This paper constructs a model of college student management and ideological and political education based on environmental psychology. The CIPP evaluation mechanism is used to analyze the appropriateness of the effectiveness of ideological and political education in colleges and universities, calculate the weight values among the indicators according to the priority relationship among environmental psychology indicators, input the evaluation data into the database information management layer for compression processing through multi-level analysis, and pass into the indicator adjustment layer as well as the data mining layer for a comprehensive evaluation of the effectiveness of ideological and political teaching, which proves that it can promote student management and ideological and political education It is proved that it can promote the integration of student management and ideological and political education. In this paper, three classes of universities were selected for the experiment, and it was proved that the average score of the ideology factor increased from 64.42 to 82.96 under the environmental psychology teaching model, and the classroom head-raising rate of students increased by more than 10%. It shows that the application of the environmental psychology teaching model to students’ Civic Education in colleges and universities can significantly improve students’ ideological and political level, can keep up with the changes in the social environment for effective management of students, and promotes the integration development of student management and Civic Education.
Research and practice on the application of computer virtual technology in arts and crafts nowadays
Authors: Huang Kun , Jiang Jianlong
Published: September 2023

With the gradual maturation of virtual computer technology, it is increasingly used in real life to represent its effects realistically. The connection between arts and crafts and digital technology is getting closer. To bring new opportunities to the development of arts and crafts, virtual reality technology and augmented reality technology is integrated to establish a 3D arts and crafts virtual design model with visualized interactive arts and crafts design as the core. In the visualized virtual scene with the support of a craft knowledge base, the coordinates of virtual design tools, original objects inside the tools, and other points are derived according to the pick-up points. By repeating “delete current scene - generate new scene”, the design of arts and crafts is realized. After the verification of properties, performance, and satisfaction, the process error of the virtual design model is only 1.57mm, the average design cycle is 5.91 hours, and the labor cost, pre-preparation cost, and design cost are 214.66 RMB, 100 RMB, and 20 RMB respectively, which are significantly lower than the traditional design mode. Furthermore, the average scoring value of designers for different forms of arts and crafts is greater than 8 points, which is more satisfying with the application effect of the model. The model is connected to design practice with the help of virtual technology, which not only improves work efficiency and saves material and labor consumption but also facilitates the optimization of design solutions and the extension of solution serialization.
Exploring the integration development path of rural tourism and rural revitalization under the perspective of self-media development and communication
Authors: Liao Yanping
Published: September 2023

With the rapid development of Internet information technology, artificial intelligence, and other emerging industries, the boundaries between industries have become increasingly blurred, showing a new trend of cross-fertilization development. Achieving industrial integration development has become an important symbol for each region to build a modern industrial system and achieve high-quality economic development. This paper constructs a fusion development path with the help of rural tourism and rural revitalization fusion bases, such as policy factors and the divided self-media model. Combined with the entropy value method to calculate the weight of each index in the integration development path evaluation system, the integration development path is evaluated. The analysis of the model’s obstacle degree and coordination degree shows that the path’s integration development behavior is an important influencing factor from 2017 to 2021, and the annual average value of the obstacle degree is as high as 55.73%.Furthermore, the average obstacle degree of revitalization industry chain extension in five years is 52.37%. The coordination degree of the integration development path has increased from mild disorder to primary coordination, with coordination degrees of 0.334, 0.435, and 0.612, respectively, with an average annual increase of nearly 15%. This fully indicates that the integrated development path of rural tourism and revitalization begins to gradually step into a mature stage under the influence of the communication vision of self-media development.
A Dynamic Export Product Sales Forecasting Model Based on Controllable Relevance Big Data for Cross-Border E-Commerce
Authors: Yang Yuzhen
Published: September 2023

To improve the prediction accuracy of export product sales, this paper constructs a dynamic export product sales prediction model based on controlled relevance big data for cross-border e-commerce to improve sales prediction’s scalability and dynamic evolution. Based on the traditional prediction model, a big data controllable clustering algorithm is used to divide the data into several macro-clusters by data dimensions to determine the number of class clusters and the location of centroids. The K-mean algorithm is used to estimate and categorize the indicators affecting the prediction online, to dig out the key factors affecting the prediction of export product sales, and to establish a dynamic prediction model. The analysis results show that the plausibility measure of the proposed model is 21.9, and the error coefficient is 5.1, which are the smaller values in the reference interval. The average prediction error ratio is 2.25%, the average confidence level is 93.05%, and the error efficiency between predicted sales and actual sales is only 0.98%. Thus, the prediction model proposed in this paper improves the prediction effect of export product sales and has high practical value.
English-Chinese translation strategies based on BERT and multi-similarity fusion of English and American literature
Authors: Ke Si Dai Ke Jiang·Ta Xi Bai
Published: September 2023

Under the background of big data development, more intelligent technologies make work and life convenient, and the traditional English-US literature translation methods and means are difficult to adapt to the fast-paced era of big data, so this paper conducts research and analysis on this problem. In terms of the English-Chinese translation strategy based on BERT and multi-similarity fusion of English and American literature, the article first introduces the concept and principle of BERT, and multi-similarity fusion algorithm then constructs the model of BERT and multi-similarity algorithm fusion, analyzes and discusses the English and American literature translation dataset respectively, and compares it with three different similarity algorithms in terms of three indicators. The data shows that BERT has the greatest effect on the accuracy rate, followed by BLEU value and Manhattan distance. Compared with the fusion of the three methods, the data analysis of a single method is better, and the three selected index values all remain above 90%, and this study is conducive to improving the accuracy and efficiency of English and American literature work, which is of great historical significance for international literary communication.
Design of an enterprise accounting system based on decision tree model
Authors: Ling Xuejun
Published: September 2023

The key to the enterprise is in management, and the focus of financial management is enterprise accounting, and the enterprise accounting management system is the core of financial management. Developing a set of accounting management systems has become an urgent problem to solve to improve the efficiency and accuracy of enterprise accounting. In this paper, we use the decision tree model to design the enterprise accounting system and establish an efficient accounting system, which is logically divided into 5 layers: database, data storage layer, business logic layer, business appearance layer and user interface layer. The effectiveness and applicability of the decision tree model for enterprise accounting systems are discussed. The results show that the decision tree model can improve the accounting error tolerance and efficiency and reduce accounting risk. The satisfaction rate of most evaluation indexes has increased to more than 50%, the satisfaction rate of accounting business operation compliance has increased from 6% to 55%, the reasonableness of the internal audit cycle has increased from 18% to 70%, and the timeliness of annual accounting statement disclosure has increased from 8% to more than 50%. The decision tree model is positive for using enterprise accounting and can meet the requirements of enterprise accounting system design.
Analysis of Ethnic Elements in Xinjiang Music Works Based on PPM Model under the Perspective of “One Belt, One Road
Authors: Yu Dawei , Liu Xu
Published: September 2023

Under the background of digitalization of big data and information, the national “One Belt and One Road” initiative has produced a new huge effect on the ancient Silk Road between Xinjiang and Eurasia, how to revitalize the traditional music culture of ethnic minorities and how to make the traditional music culture resources of ethnic minorities be effectively protected and developed in the process of protection and inheritance of intangible cultural heritage in the world? Based on the analysis of ethnic elements in Xinjiang music works based on the PPM model under the perspective of “One Belt, One Road”, this paper first introduces the concept of PPM, the Bayesian structure algorithm, constructs the PPM model, and analyzes the data using by the structural equation modeling method, and explores the evaluation of PPM model under different sample sizes and different indirect The performance of four methods, Bayesian structural equation modeling method, structural equation modeling method, classical regression method and Bayesian regression method, was evaluated for the analysis of ethnic elements in Xinjiang music works under different sample sizes and different indirect effect truth values. The results show that the standard errors under the four models become larger as the regression coefficient b between Y and X increases, but in the case of (a=0, b=0.59), the standard error of the structural equation modeling method for the analysis of ethnic elements in Xinjiang music works is 0.048, which is the smallest compared with the standard errors of other algorithms. The structural equation algorithm of the PPM model is very applicable when dealing with practical problems. It can not only be used in theoretical research but also has a great influence on realistic guidance, which has an important theoretical significance and practical value for the survival and development of the traditional music culture of ethnic minorities in China.
Design and implementation of a virtual teacher teaching system algorithm based on facial expression recognition in the era of big data
Authors: Lu Rui , Ji Feng
Published: September 2023

With the development of big data, virtual course teaching has developed rapidly. In virtual teaching, the lecturer’s position is pivotal, and the virtual teacher’s lecture mainly conveys information through intuitive facial expressions, so the effectiveness of facial synthesis is crucial. However, traditional facial expression synthesis methods suffer from local distortion and lack of subtle expressions due to driving complex topological models and delays due to large computational effort. To this end, this paper proposes a facial expression extraction method based on feature point texture mapping. First, a video face expression feature point tracking algorithm is designed. Firstly, we design a video face expression feature point tracking algorithm. We use a monocular camera to capture facial expression images, use a texture mapping algorithm to detect faces and extract face feature points, and add a time threshold processing mechanism to the relevant filtering algorithm to detect face frame tracking to realize face feature point tracking in video. Secondly, the parameters are controlled by face expression animation, including head pose and face expression parameters. The head pose is solved by the Laplace algorithm, and the head rotation matrix and translation vector are output to establish the coordinate system. Finally, the stability and real-time performance of the feature point texture mapping algorithm are verified by expression capture test and recognition effect. The results of this paper show that: in the expression capture test, the average data transmission time is about 1ms, and the total expression transmission time of each video image frame is 32ms, which is 1.23ms and 9.8ms shorter than the traditional algorithm, respectively; in the expression recognition effect test, the successful recognition rate is increased by 10.2% on average compared with the traditional algorithm; and in the application to the classroom teaching effect test, 86.6% of the students are satisfied with the virtual teacher. 86.6% of the students highly agreed with the virtual teacher teaching, and 83.3% of the students thought that the model had a positive effect on the learners’ learning, which proved the superiority, real-time, stability and practicality of the algorithm designed in this paper compared with the traditional algorithm. The research work in this paper also provides solutions to the problems of virtual course teaching.
Legal risk assessment of enterprise labor dispatch employment under clustering algorithm
Authors: Wang Weixia
Published: September 2023

In the background of the era of digitalization of data information, artificial intelligence algorithms are becoming increasingly intelligent, and the traditional enterprise legal risk assessment fits well with the requirements of the development of the era of big data. This paper focuses on the legal risk assessment of enterprise labor dispatch employment under the clustering algorithm, firstly, by reviewing the literature to understand the concept and principle of the clustering algorithm, constructing the legal risk assessment model of enterprise labor dispatch employment under the clustering algorithm, and applying The legal risk of enterprise labor contract management was assessed by expert scoring, and the risk assessment result was 62.2 points, which was a high score and its legal risk level was high and needed to be improved. The Gaussian mixture model uses probability distribution to determine the degree of similarity between samples, and the three indicators that contribute most to the effect of Gaussian mixture clustering are selected. The purpose is to identify more high-risk enterprises outside the framework of the “special treatment” system and to provide guidance on measures to prevent the legal risks of labor dispatch. Therefore, the legal risk assessment of labor dispatching in enterprises under the clustering algorithm has certain implications for business operators and academics who study the legal risk assessment of labor dispatching.
Application of random forest algorithm in the detection of foreign objects in wine
Authors: Wang Liangbo , Yang Yanzhe , Xu Liping , Ji Tao
Published: September 2023

In order to explore the applicability of random forest algorithm in the detection of alcoholic foreign matter and to improve the identification of alcoholic products. In this paper, based on the random forest algorithm, the feature values of random forest are fuzzified using the fuzzy comprehensive evaluation method, and the application model of alcohol foreign body detection anomaly based on random forest fuzzy tree nodes is established. And the reliability of the random forest algorithm is verified by the quantitative analysis of the three test indexes (i.e., recall, precision, and accuracy) and the anomaly proportion coefficient of the test data set by the algorithm in this paper. The results show that the recall, precision, and accuracy of the random forest-based anomaly detection for alcoholic beverage foreign objects are 99.65%, 95.49%, and 97.19%, respectively, and the average value of the three eigenvalues of this paper’s algorithm is 97.44%, which is 59.89%, 43.98%, and 1.92% higher than the other three algorithms, respectively. In terms of the anomaly proportion coefficient, the stability of the algorithm in this paper is the best when the coefficient takes values between [0.2, 0.6]. It can be shown that the algorithm based on random forest can be applied to the foreign matter detection of wine, and through the detection of anomalies, the quality of the wine currently undergoing detection can be clearly and explicitly analyzed, which also provides a new direction for the application of the random forest algorithm.
Application of ELM algorithm-based generative adversarial network model in network security
Authors: Wen Zhixian
Published: September 2023

To improve the efficiency and accuracy of network intrusion discrimination, this paper introduces intrusion detection techniques in a generative adversarial network model. Firstly, a basic framework of a generative adversarial network is constructed. Secondly, the generative adversarial network is trained, and the training process is analyzed to find the data discrimination point in the network. Finally, ELM (Extreme Learning) algorithm is introduced at this discriminating point. The output weight matrix is derived using the minimization square loss function and least squares regression to improve the intrusion discrimination accuracy and intrusion cracking rate in the generative adversarial network, improving network security. To verify the security of the ELM algorithm, this paper simulates the intrusion of the constructed network model, and the results show that the intrusion detection accuracy of the generative adversarial network model based on the ELM algorithm can reach 100%, which is higher than that of DCGAN network 19% and LSGAN network 23%, respectively. The intrusion cracking rate of its layer 5 neural network can reach 92% at the second 2.5 seconds of the simulated intrusion. From the above results, it is clear that the generative adversarial network model based on the ELM algorithm can accurately detect and efficiently crack the intrusion to improve the network security performance.
Research on the influence of new media on the ideological and political education of college students in the background of the Internet and countermeasures
Authors: Meng Tingting
Published: September 2023

This paper constructs a new media for college students’ ideological and political education cloud platform based on the Internet background to enrich the ideological and political education content of college students. Firstly, the online teaching system is realized through the semi-structured database HBASE module and relational database MySQL module to use; secondly, the BP algorithm is used to inform the management data of college students, and the serial mode and batch mode in the BP algorithm is used to improve the data mining efficiency, and finally, the system is tested for data. The results show that the cloud platform education system constructed in this paper can reach the highest score of 6.4 for teachers’ teaching orientation, teaching programs, and students’ recognition, with 82.4%. And the average scores of the students in the experimental group in the professional course and the Civic Science test are 10% and 20% higher than those in the control class, respectively, and the average score can reach 45.9 on the dynamics of teaching behavior. Thus, it can be seen that the cloud platform constructed in this paper helps to promote the high-quality development of the teaching of Civics for college students and effectively improve the teaching effectiveness of Civics.
Analysis of the Factors Affecting Innovation and Entrepreneurship of College Students Based on TRIZ Theory
Authors: Tao Qifu , Zhuang Xiong
Published: September 2023

This paper aims to analyze the influencing factors of innovation and entrepreneurship of college students. By studying the framework of the TRIZ theory system, this paper summarizes the common principles of entrepreneurship, realizes the construction of a conflict matrix, establishes entrepreneurship evaluation indexes, and determines the weights of evaluation indexes by constructing a judgment matrix. Then, based on the theory, the influence of each factor on the innovation and entrepreneurship of college students is analyzed in terms of participation status, main obstacle factors, personal trait influence, market influence, and social and governmental support. As for the influence of main external factors, 43.57% of students chose “shortage of funds for innovation and entrepreneurship”, 42.04% of students chose “lack of creativity and cannot find a good direction for innovation and entrepreneurship”, 37.45% of students choose 37.45% of students chose “lack of good innovation and entrepreneurship projects and innovative teams”. In terms of personal traits, innovative thinking, stress resistance, social experience, leadership and coordination, risk tolerance, self-efficacy, and self-drive all affect the decision and effect of entrepreneurship. Support from the government and society is also beneficial for college students to carry out entrepreneurial activities. Innovative entrepreneurial ability is a comprehensive ability influenced by multiple factors and needs to be considered comprehensively in the analysis.
Research on the path of enterprise management innovation based on multiple logistic regression model
Authors: Li Daoyang , Xu Shaofu
Published: September 2023

Exploring the path of enterprise management innovation is to help enterprises transform and upgrade faster and better. This paper first explains the principle of logistic regression, introduces the definition of the multiple logistic regression model, and describes the algorithm for estimating regression parameters using the great likelihood method. Then, an extreme gradient boosting XGBoost model is introduced and combined with the multiple logistic regression model; an MLR-XGBoost model is constructed to analyze the enterprise management innovation path. The MLR-XGBoost model is used to analyze the correlation between the indicators and corporate management innovation by using the MLRXGBoost model. From the data on strategic control integration and cultural reconstruction capability, the correlation of infrastructure guarantee construction capability and entrepreneurial leadership accounted for a higher percentage, 79.74%, and 61.32%, respectively. From the data on organizational structure reengineering and business process coordination ability, the correlation of implementation process standardization ability and business operation visualization ability is higher, 76.58% and 70.28%, respectively. The MLR-XGBoost model can effectively analyze the path of enterprise management innovation and help enterprises achieve transformation and upgrading faster.
A Hidden Markov Model-Based Network Security Posture Prediction Model
Authors: Yang Xiaoping
Published: September 2023

As a key technology of network security situational awareness, this paper focuses on network security situational prediction technology and proposes a new network security situational prediction model based on Hidden Markov Model. The paper proposes a network security posture prediction method based on the improved Hidden Markov Model for the problem that the Baum-Welch parameter training method of the traditional Hidden Markov Model for posture prediction is sensitive to initial values and easily falls into local optimum. The method obtains the initial parameters by introducing the simulated annealing algorithm and using its excellent probabilistic burst-jump property to find the optimal in the global range. The Baum-Welch algorithm is used to optimize the initial parameters further to obtain the optimal model parameters, and then a more accurate posture prediction model is established. The probability of occurrence of the alarm information sequence corresponding to the network security posture value of 3 at t= 4 is obtained by simulating the network environment for testing, which is 0.000268, 0.000152, 0.000147, 0.000284, and 0.000187. Comparing the generated network security posture values with the real situation, it is found that the predicted results in this paper are highly similar to the real values. It is verified that the improved Hidden Markov method can effectively improve the accuracy of the network security posture prediction model and reflect the network security situation more objectively and realistically.
The impact of the financing structure of cultural enterprises on enterprise value under the ACC payment model
Authors: Sima Honghao
Published: September 2023

To avoid financial risks, this paper validates the relationship between EV the two based on enterprise value ( EV ) as the dependent variable, and the indicators of debt financing and equity financing structure models as independent variables. Firstly, we introduce interaction terms and panel threshold regression to verify the effect of debt financing structure on enterprise value. Subsequently, a multiple regression results approach is used to verify the impact of equity financing structure on firm value. The analysis of the results shows that the impact of debt financing on enterprise value is divided into four levels at the nodes of 17.876%, 43.294%, and 74.312%, and the higher the level, the smaller the promoting effect, and the larger the inhibiting effect; the impact of equity financing on enterprise value is positively correlated with a correlation of 0.3652, and the higher the concentration of equity, the larger the promoting effect. Overall, equity financing has a greater facilitating effect and lower risk for cultural enterprises compared to debt financing, and to a certain extent, it enables enterprises to actively embrace the market, improve the product effect power, innovate and develop, and increase the growth of enterprise value.
Exploring the Practice of Cultivating Business English Talents from the Perspective of Artificial Intelligence
Authors: Hu Ruoxi , Xie Dan
Published: September 2023

In the context of the development tendency of artificial intelligence, the paper describes the opportunities and challenges artificial intelligence brings to business English talent training, innovates and reforms innovative business negotiation talent training methods, and develops independent innovation according to the future development trend of artificial intelligence. The paper discusses the practical activities of training business English talents using artificial intelligence. It mainly focuses on the indicators of building the entity model of business English talents training through artificial intelligence technical RBF ne ural network, grasping the genetic algorithm from four aspects such as the number of gender chromosomes, integral function formula calculation, genetic algorithm, RBF neural network parameters to optimize the entity model and genetic algorithm, and optimizing the limitation of RBF neural network according to the genetic algorithm. The RBF neural network entity model with the genetic algorithm is used to implement detailed analysis and scientific research exploration of the business English talent training evaluation system. The database deviation index and precision index values under the two entity models were implemented for comparison operation. The experimental results show that under the deviation index, the RBF neural network entity model, according to the genetic algorithm, converges quickly and longer than the RBF entity model. Regarding the precision index, the genetic algorithm RBF neural network has a higher precision than 0.94 for every 60 teams, while the RBF model has a precision of 0.84. This research allows for a more accurate analysis of the strengths and weaknesses of school students in business English. Teachers need to improve their academic performance and quality based on their strengths and weaknesses to facilitate the shaping of more excellent business English talents for China. It is important to explore the way of training business English talents under artificial intelligence to accelerate the innovative development of English education and training in China and the trend of English development.
Simulation analysis of asset pricing based on the Gaussian process
Authors: Nong Jingping
Published: September 2023

This paper simulates and analyzes asset pricing based on the Gaussian model, simulates stock price paths under the Heston model, B-S model, and Gaussian model using the Monte Carlo simulation method, and compares with the real path. The difference between the Heston model, the B-S model, and the real value for predicting KIA financial assets is greater than 0.6, while the difference between the Gaussian model and the real value is less than 0.25. The difference between the Heston model, the B-S model, and the true value of Shenzhen Holdings’ financial assets is greater than 1, while the difference between the Gaussian model and the true value is less than 0.35. Similarly, the difference between the Heston model, the B-S model, and the true value of Shun Tak Group’s financial assets is almost greater than 0.60, while the difference between the Gaussian model and the true value is less than 0.35. It can be seen that the Gaussian model is closer to the true value than the Heston model and the B-S model, so it is reasonable and effective to use the Gaussian model to price financial assets. This study not only presents a new basis for theoretically studying financial asset pricing but also provides a theoretical basis for applying option pricing in risk management.
Exploring the design of ecological and energy-saving residential buildings adapted to climate change based on a simulated annealing algorithm
Authors: Zhang Hui
Published: September 2023

In the context of the digital development of big data and information in recent years, performance-based residential building design and its optimization methods have gradually become a research hotspot of domestic and international attention. The simulated annealing algorithm is a major component of residential buildings’ optimal energy efficiency design. Although the crossover operator under the computational traditional simulated annealing algorithm incorporates the respective advantages of the genetic algorithm and simulated annealing algorithm, the purely optimal genetic simulated annealing algorithm is more effective for the evaluation of index analysis and better reflects the superiority of the algorithm. In the Energy Plus model, the three algorithms were used to analyze the design indexes of ecological energy-efficient residential buildings, and the SS values of the MOSA algorithm fluctuated between 10% and 24%, and the performance of the recommended genetic simulated annealing algorithm was significantly better than the other two algorithms. This study effectively solves the difficulties of low efficiency and high failure rate common in design practice when using this technique and is of historical importance to the development of energy-efficient residential buildings in China.
Research on the implementation path of industrial structure optimization in Fujian Province under the goal of “double carbon”
Authors: Zhu Yanling , Liu Chen , Yue Dazhi , Xie Jiemeng
Published: September 2023

Facing the dual pressure of domestic environmental pollution and international climate change mitigation, China, the world’s largest emitter of carbon emissions, has proposed a “double carbon” target of 3060. Fujian Province is a clean energy province and a major economic province in southeastern China, with inherent energy conservation and emission reduction advantages. However, as industrialization is still in progress and urbanization is accelerating, the problems of low industrial level and sloppy development are still prominent, and the future low-carbon transformation will be difficult and long. Based on the theory of industrial structure optimization and the theory of low carbon economy, this paper analyzes the influence mechanism of industrial structure optimization on carbon emission from three perspectives: efficiency improvement, technological progress, and structural adjustment. Secondly, an econometric model is constructed by combining the environmental Kuznets curve, and the time series data of Fujian Province from 2000-2021 are analyzed empirically to derive the optimization path of industrial structure on carbon emissions in Fujian Province through co-integration analysis, multiple regression, mediating effect analysis, and robustness testing methods. The results of this paper show that from the structure of energy consumption in Fujian Province, coal and oil consumption account for 72% of the total consumption, which is the main cause of carbon emissions in Fujian Province. The mediating effect and stability analysis of the optimization path through the benchmark regression model shows that the p-value variance is 0.0862, and there is no significant difference between them. The optimization path proposed in this paper has significant utility for carbon emission reduction, improves the efficiency of energy use, strengthens the introduction of FDI and industrial structure optimization in various regions of Fujian Province in a targeted manner, and provides a reference for decision-making for global industrial structure optimization and upgrading.