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With the rapid development in the field of artificial intelligence and the advancement of deep learning theory, vehicle target detection technology has been widely used in the field of urban intelligent transportation and automatic driving, assisting vehicles to achieve safe driving in complex driving environments and improving traffic safety. This paper proposes a dynamic fuzzy image processing method based on Wiener filter and generative adversarial network, and constructs a UNIT-based de-fogging and de-raining algorithm, which can be generalized to clarify the targets obtained in rainy and foggy scenes. Then design the local perception enhancement vehicle detection model assisted by image rain removal to realize the accurate detection of vehicle targets in rainy and foggy scenes. By applying the method of this paper on the synthetic dataset Rain Vehicle Color-24, the results demonstrate that the mAP values of this paper’s method are 3.73%, 2.23% and 1.19% higher than those of Da-Faster, SA-Da-Faster and SMNN-MSFF respectively, which are able to improve the vehicle color recognition task in rainy and foggy scenes with good Accuracy. Therefore, the method in this paper can reduce the domain differences of the model in the target domain and improve the localization accuracy.

Residents’ consumption level is increasing, e-commerce vocational education has become an increasingly important field of education, how to realize customer value-added has become the focus of attention of e-commerce platforms. In this paper, we use the improved dynamic RFM customer segmentation model based on K-Means clustering to segment e-commerce consumers, to accurately portray the changes of e-commerce consumers’ loyalty and the transfer characteristics between e-commerce consumers’ groups, to achieve the identification of consumers’ online behavioral patterns. The RFM model classifies users into four categories: important value, general value, focus on development, and focus on retention. The important value users of Product B have high activity and contribution, but very low loyalty, which indicates that there may be group purchasing behaviors in this group, and the e-commerce operator of Product B can focus on serving this type of customers. After implementing the technique in teaching, the six dimensions of the experimental class C about teaching effectiveness are better than the other two classes, which shows that the technique provides a new perspective for the improvement of teaching effectiveness in e-commerce education.

Existing civil engineering professional civic education recommendation system is difficult to realize the accurate recommendation of civic resources in the process of practical application due to the lack of effective analysis of students. Taking this difficulty as the starting point, this paper improves the similarity calculation methods of user-based and content-based recommendation at the same time, and constructs an optimized hybrid recommendation algorithm. Subsequently, the effective integration of civil engineering specialty and Civic and political education under the recommendation algorithm of this paper is explored. The H value of this paper’s algorithm is in the range of 18.45-21.88, the M value is in the range of 1.85-2.01, and the D value is in the range of 4.40-4.85, which has high stability and high level of recommendation quality. Applying this paper’s recommendation algorithm to actual teaching, in which P=0.02<0.05 of the post-test test results of the values of the students in the experimental class and the control class show significant differences. It shows that the recommendation algorithm in this paper can realize the accurate recommendation of the Civics resources by combining the students’ characteristics.

Aiming at the voltage control problem of inverter-interfaced distributed energy resources in microgrid systems, this paper proposes an optimized design scheme based on coherent drafting control. The distributed energy is divided into multiple subsystems through cluster division to form a hierarchical control architecture. Within the cluster, a distributed optimization algorithm is used to achieve fast voltage convergence to the target value. Meanwhile, a coherent drafting control strategy is introduced to enhance the synergy between clusters and improve the overall stability of the system, and the optimization effect is evaluated using the voltage retention index (NVRI). The results show that the method can effectively maintain the system voltage stability under the situation of large fluctuations in distributed energy processing. In addition, the analysis of the two optimization cases of “minimum interaction with the grid and minimum operating cost” reveals that after the optimization of the system in this paper’s method, the power interaction with the grid is reduced by 3,168.542 KW, and the optimization performance is improved by 73.92%; the daily operating cost of the system after this paper’s method is significantly reduced under this condition (1229.47 yuan), and the economic efficiency is improved by 4.51%. It can be seen that the method of this paper improves the reliability and economy of the distributed energy system, proves the effectiveness of the control strategy of the method of this paper, and provides a new idea for the voltage control of distributed energy at the substation inverter interface.

In order to further enhance the effectiveness and scientificity of career planning education for students in colleges and universities, cultivate students’ awareness of career planning and improve their career planning ability. This paper designs a career planning service platform based on cloud computing. The platform realizes the management of student information in different modules according to different cloud services by analyzing the needs of resource management, interaction, growth tasks, and personal growth that are necessary for students’ career planning. In addition, the association rule algorithm in the data mining algorithm was applied to the design of the platform as a way to analyze the association between students’ interests and career skills. The multidimensional association rule algorithm mined out the main association rules that existed between students’ interests and vocational skills in the three categories of S2S, D2S and D2D. It was found that career identity shows a decreasing trend with grade level, and there is a correlation between the five dimensions of career expectations, career emotions, career awareness, career will, and career behaviors and tendencies Career planning service platform mines out the deficiencies in students’ career planning, and provides help for teachers and school administrators to provide students with reasonable guidance on career planning.

English teaching is an important part of cultivating high-quality skilled talents and one of the main positions for spreading Chinese culture. This paper proposes a teaching strategy to integrate Chinese traditional culture into the English curriculum, and at the same time, combined with artificial intelligence technology, it constructs a Dynamic Key-Value Memory Network (DKVMN-F) based on forgetting behaviors in sequences and a Neural Network-based Recommendation Model for Similar English Topics (HANN), which realizes the in-depth tracking of the students’ English knowledge level and personalized and intelligent recommendation of English topics. On this basis, a game task-driven English teaching model based on learner profiles is innovatively designed. Compared with current knowledge tracking models, DKVMN-F performs more accurately in tracking students’ knowledge mastery status and has better prediction performance by introducing features such as repetition interval and number of past answers for modeling. On both the ML-1M and Gowalla datasets, the HANN model achieves a performance improvement of 0.5%-7.5% relative to the other models. On the ASSISTments2009 dataset, the HANN model achieves the optimal value in all evaluation metrics by adding an exercise similarity attention mechanism. The research in this paper provides a teaching model reference for the use of artificial intelligence technology to realize the organic integration of traditional culture and English teaching and to improve the teaching effectiveness.

The article firstly combed the relevant factors affecting the effect of brand promotion of agricultural products, and after collecting the relevant data, it used principal component analysis to reduce the dimensionality of the characteristic factors affecting the effect of brand promotion of agricultural products. After determining the factors influencing the effect of agricultural brand promotion, the assessment model was established by using the multiple linear regression model, and the assessment test and model fitting were carried out on the model. The main findings of the article are: in the principal component coefficient matrix analysis, the three indicators of cycle continuity, product reliability, and information exhaustiveness are the first principal component, and their contribution rate is 42.24%. Project innovativeness, cycle continuity, product reliability, information exhaustiveness, project word-of-mouth, initiator’s word-of-mouth, financing effect, and number of initial fans all positively influence the effect of agricultural brand promotion.

With the rapid development of science and technology, the application of wearable devices and intelligent technology in college sports soccer teaching has gradually become a research hotspot. This paper proposes a soccer action recognition and skill level assessment model based on FSR and gyroscope sensors, using FSR and gyroscope to collect pressure and angular velocity information. The discrete degree is used to determine the athletes’ leg movement state. The time domain features and frequency domain features in the collected athlete data are extracted, and the two different features are used as training samples. Ankle-based posture angle model and SVM classification algorithm model are used to recognize the movements of soccer players and evaluate their soccer skill level. The algorithm is combined with the Beidou smart bracelet. A soccer training system integrating multiple functions of localization, heart rate detection and action recognition is designed. The recognition accuracy of this paper’s method in several soccer experiments is 100%, which significantly improves the accuracy of traditional action recognition algorithms. The soccer training system provides targeted training suggestions to help students quickly master the training essentials of soccer movements, which significantly improves their soccer skill level. With further progress in technology, the system is expected to be useful in a wider range of physical education teaching scenarios.

Archives are an important part of information resources, a witness and record of history, and a reference basis for decision-making on future development. The article applies data mining technology to college archive information service, and conducts research on the upgrading of college archive management informationization. After the modular construction of university archive management information system, the blockchain-based digital archive traceability sharing scheme is proposed to realize the encryption processing of archive information. And the calculation formula of information gain rate in C4.5 algorithm is approximated and simplified to optimize the cumbersome calculation process of attribute selection in the tree building process. The C4.5 algorithm is applied to the university archive information service system to categorize the archive information. Applying the C4.5 algorithm to college records management, the degree of influence of each customer’s information on the frequency of visits is “identity”, “age”, “specialty”, “Gender”, and customers can be categorized into frequent and infrequent customers. In the transaction throughput analysis experiment of PAPBFT consensus algorithm, it is found that the throughput of traditional PBFT consensus algorithm gradually decreases with the increase of the number of nodes, and the consensus algorithm in this paper increases the throughput with the increase of the number of nodes N, which effectively mitigates the problem of the obvious decrease in throughput caused by the increasing number of nodes. This paper efficiently and safely realizes the upgrading of university archive management informationization.

In the context of the new era, how to protect and inherit the traditional ceramic art so that its sustainable development has become an urgent problem. In this paper, we apply the technology related to the three-dimensional reconstruction of the scene to generate a three-dimensional point cloud model of the scene and realize the three-dimensional reconstruction of the target. Subsequently, the three-dimensional scene is entered through Leap Motion, and pottery learning is carried out through gesture interaction, and the SENet module is embedded on the basis of the DenseNet model to improve the accuracy of gesture recognition in the pottery process. Evaluating the results of the design practice from the visual elements of the scene space, in terms of modeling form, the average scores of the anteroom area, experience area, and the end hall area are 8.265, 8.425, and 8.945, and the morphology modeling design scheme of these three areas is more excellent, which can provide a design reference. The majority of the test audience got full scores in the pottery gesture learning, in which 16 people got full scores in the two movements of downward pressure and upward lifting respectively, and the number of full scores was more than 50%, and the design of the pottery interactive system helps the audience to understand the production process of traditional pottery.