The process of innovative education is not only a purely intellectual activity process, it needs innovative emotion as a driving force, such as strong interest, strong passion, the motivational function of evaluation, harmonious teacher-student relationship and other non-intellectual factors cultivation, in order to obtain a comprehensive effect. This study is oriented to the intelligent distribution platform of journalism and communication content to study its teaching value and innovation emotion. The Information Adoption Model (IAM) was adopted as the theoretical basis for the study of content intelligent distribution platforms, the characteristics of the platforms were summarized, and the impact of the platforms on teaching value was studied using regression analysis. The result table of the study found that the content intelligent distribution platform’s exhaustiveness, readability, and objectivity had a significant positive correlation on the usefulness of educational value, and that the influence of interactivity on perception and participation did exist and had a certain impact on educational usefulness. Finally, this paper also takes S colleges and universities as an example to assess and calculate the innovative emotion and innovative ability of the platform’s teaching value, further analyzes the teaching value of the intelligent distribution platform, and provides suggestions for the cultivation of the innovative emotion in combination with practical research.

As one of the important stakeholders in ecotourism, community residents play a crucial role in ecotourism development. This study takes interactive emotional cognition, social exchange theory and the concept of psychological carrying capacity as the guiding theories, and designs the community residents’ questionnaire from the aspects of emotional cognition and psychological carrying capacity, respectively. Correlation analysis and regression modeling were used to test the influence of interactive emotional cognition on the psychological carrying capacity of ecotourism community residents. The calculation results show that the psychological carrying capacity of ecotourism community residents is positively correlated with positive interactive emotional cognition (r>0) and negatively correlated with negative interactive emotional cognition (r<0). It was also found that community residents' proud emotional perception of tourism development had the highest degree of influence on the psychological adjustment capacity variable (R²=0.299). This study verifies the mechanism of community residents' interactive emotional cognition on their psychological carrying capacity and enriches the theoretical research on promoting ecotourism development.

This paper improves the prediction accuracy of financial crisis of listed companies by optimizing the traditional Z-score model and taking the financial warning indicators as the input features of the neural network. The study selected the financial data of listed companies in a certain place from 2017 to 2023 as a sample, compared and analyzed the early warning performance of multiple traditional machine learning algorithms with this paper’s method, and assessed the reliability of this paper’s model in the early warning of financial quality by combining with cases. The neural network-based Zscore model has an AUC value of 0.914 on financial quality early warning, which is close to 1, and the prediction results are reliable. The model’s overall financial quality early warning accuracy in year t-1 is elevated by 16.61% to 19.35% compared with the comparison algorithm, and has a faster error has convergence speed. The Z-value calculation predicts that three companies will appear to have financial quality risk in 2017, which is consistent with the actual results. The algorithm of this paper predicts that company 9 has a Z-value of 3.79 in 2031, which may have financial quality risk. The results of this paper are reliable and show the early warning method of financial quality of listed companies in a new perspective, which is an important reference value for investors and managers.

Aiming at the difficulties faced by traditional industries, this paper formulates a smart blockchain solution for sustainable industrial digitalization. Through the theoretical analysis of blockchain technology integration into industry, it provides theoretical support for the application of intelligent blockchain technology in industrial digital transformation. Combining the above three algorithms and the actual situation of industrial digitalization development, an industrial digital transformation scheme integrating intelligent blockchain technology is designed, and a case study of the scheme is conducted. The delay mean value of this paper’s scheme is within the allowable range at the maximum throughput, indicating that the scheme can promote the sustainable development of industrial digitalization. In the actual application scenario, the CD-PBFT consensus algorithm performs more prominently, and in addition, it can be seen that the industrial blockchain solution, which can enhance the product recycling rate, well practices the concept of sustainable development.

The emergence of artificial intelligence has changed the traditional visual communication design mode to a great extent. This study aims to conduct an in-depth theoretical discussion and empirical analysis of the intersection of artificial intelligence and visual communication design, for the generative design application of AI technology in visual communication design, based on the AttnGAN algorithm, designing the adaptive word attention module and feature alignment module, constructing the ACMA-GAN text image generation model, and evaluating its visual communication design by combining quantitative and qualitative experiments to assess its The effect of ACMA-GAN on visual communication design is evaluated by combining quantitative and qualitative experiments. Combined with OLS algorithm, the empirical analysis of the effect of AI technology on visual communication design is carried out, and the ACMA-GAN model achieves excellent performance in the evaluation of assisted visual communication design, with the BLEU-3 and CIDEr scores higher than the next highest scores by 7.48% and 7.35%, and the average scores of each qualitative index are over 4.5, which indicates the feasibility and good utility of AI technology in assisting visual communication design. AI technology can positively act on visual communication design through image recognition and analysis, image generation and creation assistance, personalized design and workflow optimization.

This paper adopts research methods such as literature method and questionnaire survey method to take the cultural inheritance and development of Lanzhou Taiping Drum as the research object, and conducts in-depth discussion on the characteristics, social background and development of Lanzhou Taiping Drum. The research and analysis of the influence of the inheritance of Lanzhou Taiping Drum was also carried out by using principal component analysis and stepwise regression method in combination with the actual situation. It is found that many factors of Lanzhou Taiping Drum itself and government factors have significant influence on its inheritance. On the basis of the results of this study, we explore the ways and contents of the protection and inheritance of Lanzhou Tai Ping Drum, and put forward the digital inheritance of Lanzhou Tai Ping Drum and the path of cultural ecological reconstruction in terms of the influencing factors.

In today’s digital era, user interface (UI) design is crucial for enhancing user experience and strengthening user engagement. The study uses heatmap analysis, K-means clustering algorithm and random forest regression algorithm to comprehensively analyze the characteristics of user behavior in UI pages. The predicted results of user behavior in UI pages are visualized and analyzed through heatmaps. Cluster classes are divided according to user behavioral characteristics to generate user profiles with the same behavior. Combine Random Forest and Logistic regression algorithm to get the key indexes of UI optimization design and predict their impact on user behavior experience. The research results show that the MAE and SMAPE values of Random Forest regression algorithm on user behavior prediction are 133.55 and 8.18%, respectively, with an R² of 0.96, and the accuracy rate of behavior prediction is more than 80%, which shows a good performance of user behavior prediction. The clustering algorithm divides the user behavioral characteristics into 6 clusters based on their behavioral characteristics, including cluster class 1 (browsing and exploring class), which accounts for 11.5% of the number of investigators. The weight of the top 8 of the importance of UI optimization design obtained by the random forest regression analysis algorithm is 70.26%. And the user behavior experience can be improved by 5.377~9.925 times when each element is improved by one unit.

This topic obtains the data of featured vocabulary under the technical architecture of big data platform and saves it in the form of dataset. Standing on the perspective of the principle of translation of featured words in foreign propaganda, the improved K-means algorithm and attention mechanism are utilized to design the translation model of featured words. The model of this paper is validated and analyzed from two aspects, namely, performance indexes and application effect, respectively. In the six performance indexes, this paper’s model performs better compared to the other two control models. After the experience, the control group and the experimental group show a significant difference, i.e., the introduction of data mining algorithm is more effective in translating the featured vocabulary on the traditional model.

The development of artificial intelligence has brought new development opportunities for modern enterprises, but employees present a certain degree of resistance to the introduction of AI technology. The author tries to dissipate employees’ resistance and improve their acceptance of AI through organizational training. After researching organizational training and employees’ perceived awareness of AI, organizational training and employees’ acceptance of AI are taken as antecedent and consequent factors to construct a structural equation research model of the two. The research hypotheses are proposed based on the theoretical study of the two. Regression analysis of the effect of organizational training on employees’ AI acceptance is conducted through structural equations. The regression results show that training investment, employee motivation and knowledge training in organizational training all have a significant positive effect on both employees’ AI perceived ease of use and AI perceived usefulness. Employee AI perceived ease of use and AI perceived usefulness have a positive effect on employee behavioral intention to use AI for knowledge creation and automation. Employees’ behavioral intention to use AI for knowledge creation will have a positive effect on AI for knowledge creation, and behavioral intention to use AI for automation will have a positive effect on AI for automation.

New energy vehicles have a broad market, and the pricing and after-sales service of new energy vehicle enterprises have become the effective competitiveness of new energy vehicle enterprises. Therefore, this paper studies the pricing and after-sales service decision-making of new energy vehicles on the basis of game theory, and the study first gives a brief overview of game theory. Then, in the context of new energy vehicle subsidies, the optimal pricing under different sales modes is studied using game theory models. It also studies the utility of service stores of the same level of new energy vehicles with the support of game theory, and finally puts forward service suggestions from four aspects: optimizing offline service stores, expanding online services, developing service projects, and developing personalized services. This study can also provide valuable references for the pricing and service marketing of new energy vehicle enterprises, improve the competitiveness of after-sales service at the same time, and also put forward feasible suggestions for the future after-sales marketing methods of new energy vehicle manufacturers.