The effective integration of intelligent interaction design and visual communication design education is an important attempt to improve the educational effect. This paper firstly constructs the evaluation system for the teaching effect of intelligent interaction design and visual communication design courses, and then establishes a set of evaluation models based on fuzzy logic inference algorithm. In the example application part, the G1-entropy weighting method designed in this paper is used to measure the weights of each influence index, followed by an empirical study using School A as an example, and finally the multiple linear regression analysis is used to make further exploration on the influencing factors of the teaching effect of the course. The study concludes that in the subjective weight calculation experiment, it is found that the weight of external influences accounts for the highest proportion of 0.277, that is, experts believe that the overall planning has a strong influence on the course effect. Further, the regression modeling yields that learning interest, curriculum, faculty, teaching content, and practical activities have significant positive correlation with teaching effectiveness.

Influenced by the backward management methods and other factors, the integration and sharing of digital educational resources in colleges and universities have certain problems, and cannot give full play to the advantages of digital educational resources in colleges and universities. Based on this, this study proposes a targeted digital education resources integration strategy, using particle swarm algorithm to optimize the sorting of digital education resources, to obtain high-quality digital education resources, introducing fuzzy clustering algorithm and combining with the principle of decision tree, to accurately classify and integrate digital education resources. On the basis of realizing the integration and classification of digital educational resources, a digital educational resource sharing model is formed to promote the effective use of digital educational resources. The digital educational resources integration strategy proposed in this paper is adopted to carry out the application practice of digital educational resources integration and sharing in S colleges and universities. The mean values of the three dimensions of students’ learning attitude, teachers’ teaching, and teaching effect in S colleges and universities reached 3.48, 3.97, and 3.74, respectively, and this paper’s digital educational resources integration strategy method has a positive positive impact on the dimensions of students’ learning attitudes, teachers’ teaching, and teaching effect in Civic and Political Education in S colleges and universities.

With the development of globalization, the cross-cultural market is facing needs such as diversification and personalization of consumer demand. Based on the theory of market segmentation, the study proposes an ant colony algorithm to improve the market segmentation model of K-means clustering, and examines its effectiveness. Further, a personalized recommendation algorithm based on multivariate dynamic user profiles is proposed to recommend products to target users more accurately. A reliable simulation environment is constructed based on the KuaiRec dataset and the classical LastFM dataset to properly evaluate the performance and effectiveness of the model on the recommendation platform. Through the K-means ant colony clustering algorithm proposed in this paper to divide the interest information and attribute information of users, the users as a whole are classified into specific categories, and the online_reward value of the personalized recommendation algorithm based on multivariate dynamic user profiles proposed in this paper fluctuates from 50.05 to 50.49, which is a significantly superior performance. As a result, this paper concludes that crosscultural marketing strategies should be marketed at four levels: product, price, channel, and promotion, in order to adapt to regional cultures, attract consumers, and build consumer loyalty and satisfaction.

Consolidating and improving supply chain resilience and maintaining supply chain stability and security is an important foundation for promoting the realization of high-quality development. After initially selecting supply chain resilience related indicators, the research is screened and downgraded through factor analysis to establish a supply chain resilience evaluation index system. Subsequently, based on the model integration framework, the supply chain toughness evaluation model with improved Stacking integration model is constructed on the basis of a single machine learning algorithm and an integrated learning algorithm, and the model parameters are adjusted and optimized through the learning curve to achieve the optimal evaluation effect and compared with the existing model. The results show that the Stacking supply chain toughness evaluation model constructed in this paper has a relative error of 23% or less in 3685 enterprise samples and accounts for 98.78%. It shows that the Stacking integrated model established in this paper has good prediction effect and high accuracy, which has certain value and significance to the research of supply chain toughness prediction, and can provide scientific reference basis for enterprises.

Taxation, as one of the rigid expenditures of enterprises, directly affects the production and manufacturing costs of enterprises, and influences their disposable income as well as the improvement of economic level. Based on the data of Shanghai and Shenzhen A-share listed enterprises in China from 2013 to 2023, the study explores the impact of corporate tax burden on economic development based on multiple regression models, and conducts robustness tests by double-difference and reduced-sample methods. The study finds that corporate tax burden has an inverted “U”-shaped impact on economic development, which is positively correlated with economic development when the corporate tax burden is at a low level, and negatively correlated with economic development when the corporate tax burden crosses the most critical point. In addition, in the heterogeneity test of emerging and non-emerging advantageous industries, the tax burden and the high-quality development of enterprises show an inverted “U”-shaped relationship, but the inflection point of the emerging advantageous industries will appear earlier.

Asphalt as a common material for urban road construction, asphalt pavement has been favored by the municipal industry because of its good wear resistance and stability. This paper identifies the raw materials for this study, and obtains the samples for this study under the technical guidance of the preparation process. In order to more intuitively observe the role of the two, the construction of two-dimensional numerical model, and with the help of water-immersion Marshall test, freeze-thaw splitting test, rutting test, trabecular bending test, together to explore the effect of compounded fibers on the performance of modified asphalt mixtures. When 6% SBR was added on 2% ZnO+4% DTDM, the flexural strength modulus increased from the initial 5482.76 to 6217.54 MPa, and its increase was 18.53%, which indicates that the addition of fiber has a promoting effect on the flexural properties of modified asphalt mixtures.

This study takes the intelligent transportation information management system as the basic framework and focuses on the technical scheme of the traffic flow regulation module in the system. Taking the intersection in urban traffic as the research scenario, we extract the characteristics of urban traffic time and regulation objective function to construct the traffic flow scheduling model. The particle swarm algorithm (PSO) is used to optimize the traffic flow control model, and the inertia weights and the four degree and position update mechanism are improved for the problems of PSO algorithm, such as easy to fall into local optimization. The improved particle swarm algorithm (MPSO) in this paper is utilized to solve the traffic flow scheduling problem, and compared with the PSO algorithm to highlight the effectiveness of the improved operation in this paper. The results show that the optimized traffic flow regulation model based on MPSO algorithm has significant performance advantages in indicators such as average parking delay. Compared with the PSO algorithm, the MPSO algorithm in this paper obviously has higher convergence accuracy and can achieve more excellent regulation solution set in the intersection traffic scheduling scenario. The application of the method in this paper can effectively solve the problems of vehicle congestion and frequent traffic accidents in urban intersections.

In recent years, China’s health insurance drug negotiation has become increasingly improved, and the speed of access to the health insurance catalog has increased dramatically. Under the implementation of health insurance negotiated drugs and dual-channel policy, this study investigates the application of negotiated drugs in a certain region to explore their accessibility and affordability. On this basis, it links the health insurance department, designated pharmacies and medical institutions to explore the precise regulatory mechanism of dual-channel drugs in health insurance. For the drug safety supervision therein, collaborative filtering algorithms, attention mechanisms and multi-task learning are utilized to construct an adverse drug reaction prediction model. It is found that under the influence of the health insurance dual-channel policy, the accessibility and affordability models of medicines are enhanced, the types of negotiated medicines, the number and total amount of purchases are increased year by year, and the total amount of purchases by medical institutions and retail pharmacies are enhanced by 3.42 times and 2.36 times, respectively. The proposed prediction model has good accuracy and applicability in predicting adverse drug reactions, with AUC and AUPR values of 0.93 and 0.83 on different datasets, which are better than the comparison methods. It is recommended to continuously promote the construction of the “dual-channel” management mechanism of designated medical institutions and retail pharmacies to enhance the convenience and sense of access to medical care of the insured. x

The enterprise financial risk under the new era economy exists in all aspects of enterprise operation, thus this paper screens the enterprise financial risk early warning indicators from the four aspects of enterprise profitability, operation ability, development ability, and debt repayment ability. The logistic Steele model is introduced to optimize the population size function of differential evolution algorithm to achieve the dynamic adaptive population size. Then the adaptive differential evolution algorithm is used to optimize the threshold value of BP neural network, and the neural network prediction model based on the improved differential evolution algorithm is derived. Analyze the operation steps of the improved differential neural network algorithm model in enterprise financial security detection to realize the optimal solution of the enterprise financial risk warning model. Compare and analyze the predicted value of the improved differential neural network algorithm model with the real value of the enterprise financial development, and analyze the use of differential evolutionary algorithm in the prediction of enterprise financial risk.The prediction error of the net asset growth rate of enterprise Q in the 1st quarter and the 3rd quarter of the year 2024 is 0.0119 and -0.05309, respectively, with a smaller absolute value of the error, and the improved differential neural network algorithm is able to effectively predict the corporate financial risk.

In recent years, foreign research on the optimal allocation of supply chain resources and operational coordination in the digital economy environment has also made more and more progress, and the current status of domestic research is in the development stage, and supply chain management in the context of the digital economy has become another research hotspot. In this regard, this paper studies the application of Hamiltonian circuit in supply chain resource allocation from three aspects, such as product pricing strategy, supply chain management optimization and consumer behavior, and constructs the optimal resource allocation model according to the steps of resource allocation establishment. Through the Hamiltonian loop algorithm, the revenue function of cross-border ecommerce supply chain services is obtained. Using the Hamiltonian loop algorithm, the optimal price model of supply chain logistics is simulated and simulated experiments are carried out, and the optimal logistics and distribution services will be priced at about 225 under the high competition situation with competition coefficient k  0.6 . Under the optimal allocation of supply chain resources, analyzing the user’s satisfaction, retail customers’ satisfaction with the supply of goods in 2021 is 81.806 points, higher than the province’s 0.913 points, and the experimental results show that the resource allocation model can meet the needs of the customers, making the supply and demand of the product resources more balanced, which argues the scientific nature and reliability of this study.