This paper draws a framework for constructing user demand modal information, uses crawler technology to obtain online review text information, processes the text information, and mines relevant consumer demand information. The LDA topic model is used to extract the topics of consumer concern from the online comments, identify the topics of consumer demand and clarify the concern degree of each demand. The KANO model is proposed to establish a consumer demand classification method based on the KANO model by combining product characteristic attributes and consumer demand information. Examine the theme discrimination performance of the LDA model on the hotel category, footwear category, and food category datasets. Combine the preprocessed user demand data to statistically quantify user demand for quantitative Kano transformation. Classify user demands into Kano categories and calculate the priority order of user demands to get the product optimization strategy. The weighted order of consumers’ demands for automobiles is footrest, cigarette lighter, antenna, window, low beam, key, etc. in order. It can be found that automobile consumers pay more attention to the needs of antenna, cigarette lighter, pedals, and enhancement of accessory functions. As a result, automobile manufacturers should increase the seat comfort, improve power, enhance the flexibility of shifting such aspects of the whole vehicle handling experience, in addition to improving the lights, keys and other car quality related needs.

Answering the spatial relationship between ESG ratings and total factor productivity of enterprises can provide a reference for the high-quality development of macroeconomy and the sustainable and healthy development of enterprises. In this paper, the improved K-means algorithm-PCA-K-means is used to measure the principal component data corresponding to the economic development level of 26 central cities, based on which and cluster analysis is conducted to classify the regions and city types of East, Central and West China. Furthermore, benchmark regression and spatial heterogeneity analyses were conducted using a fixed-effects model. The study shows that ESG ratings have a significant positive relationship on firm-wide factors. Observing the PCA-K-means clustering results, it can be found that there is no significant positive effect between the economic development speed and the ESG ratings of enterprises, which indicates that there is a difference in the impact of ESG ratings on the total factor productivity of enterprises in different regions. Therefore, the spatial heterogeneity analysis shows that the correlation coefficients of ESG rating performance in the central and western regions are 0.0163 and 0.0275, respectively, and ESG rating performance has a greater impact on enterprises in the central and western regions compared with the eastern region. The effect of ESG rating on total factor productivity of enterprises in resource-dependent cities and old industrial bases is not significant.

Due to the development of advanced information technology such as artificial intelligence, the traditional marketing profession is being transformed and upgraded in the direction of intelligent higher vocational marketing, and the requirements of marketing positions on the knowledge, quality and ability of practitioners have changed. The article analyzes students’ cell phone online behavior in different classrooms based on DBSCAN clustering algorithm by collecting students’ campus network usage data, according to which the results can provide an effective basis for school management. By introducing the Interpretive Structural Model (ISM) and analyzing the interrelationships between courses, the article proposes a course cluster division scheme for marketing majors, which provides methodological support for the division of clusters in the construction of course clusters for professional teachers, as well as the selection and organization of the courses within the clusters. Finally, investigate the differential judgment of students from different places of origin about the influence of teaching environment, teacher quality, teaching process, teaching tools and resources on the teaching effect of marketing courses, the data show that the influence factors of marketing course teaching have obvious differences in the influence of the teaching effect of the course, improve the ability of professional teachers to educate people, optimize the teaching process of the marketing course, and deepen the reform of classroom teaching.

In the current fields of quantum information processing and quantum computing, fast and accurate quantum state manipulation and preparation have been of keen interest to researchers, and their potential applications are mainly in quantum measurement, quantum information, quantum communication, and quantum sensing. In this paper, the Hilbert space of a bipartite state system is unfolded by four Bell state entanglement bases and the result is projected to the subsystem to obtain a mixed state. A quantum approximation algorithm is proposed to provide a solution to the combinatorial optimization problem, and based on the workflow of the quantum approximation optimization algorithm, an improvement is proposed to the quantum approximation optimization algorithm to solve the constrained problem using the quadratic unconstrained binary optimization method. Based on the theory of cavity magnetism, the hybrid quantum system model is constructed, and the calculation method of Hamiltonian quantity is proposed. Combined with the quantum entanglement optimal path calculation of UQAOA algorithm, the optimal value of time-microwave entanglement is obtained at r=0.234, so the compression parameter r=0.2 is used in the calculation. Based on the UQAOA algorithm for the analysis of the transmission characteristics of the generated OMA wave in air and the transmission optimization problem, the simulation obtains the reflection coefficient is slightly lower than that of the test, and the maximal error error is controlled at ±7.5dB around, and the two results are basically in agreement.

The organic combination of traditional rule of law culture and Civics education in colleges and universities is a breakthrough to improve the effectiveness of Civics education. Focusing on the Civic and political education that integrates traditional rule of law culture, the article introduces virtual reality technology and differential evolution algorithm to explore the course effect optimization method of Civic and political virtual reality teaching, and obtains the optimal content applied to the corpus through differential evolution algorithm according to the content characteristics of Civic and political education. On this basis, the evaluation index system is constructed to assess the course optimization effect of Civics virtual reality teaching. Example validation shows that the Civics corpus based on differential evolutionary algorithm and the proposed Civics virtual reality teaching method achieve better Civics course optimization effect, with an overall score of 3.833, and have the ability of practical application. Students of different genders and grades show significant differences (P<0.05) in the evaluation results of most of the first-level indicators. The application section of virtual reality technology promotes the teaching effect of traditional rule of law culture into the ideological education of colleges and universities.

The research in this paper mainly focuses on the design of the quality assessment system of Ideological and Political Education to realize the innovation of Ideological and Political Education mode. The principal component analysis algorithm is used as the core algorithm of the assessment system, and combined with the system architecture model of hierarchical design, it realizes the collection, processing, analysis and assessment of the data on the quality of Ideological and Political classes. The research results show that the assessment system based on principal component analysis algorithm in this paper has a higher accuracy rate of education quality assessment compared to the evaluation system based on a single deep learning algorithm such as RBF neural network. At the same time, the system in this paper also has a higher assessment accuracy than the evaluation system using a combination of algorithms, and shows excellent stability performance when assessing the educational quality of 150 teachers. Using this system to assess the quality of Ideological and Political Education of 8 teachers, the comprehensive ranking is more reasonable than the original ranking. The Ideological and Political education quality assessment system designed based on the principal component analysis algorithm in this paper has a far-reaching impact on the innovation and intelligent development of the Ideological and Political Education model in the digital era.

The development of electronic and electrical architectures towards domain centralization makes it difficult for traditional distributed control architectures to meet the functional needs and performance requirements of increasingly complex intelligent devices. This study utilizes a multi-model adaptive control algorithm to assist the domain controller to adjust the control parameters in real time according to the state of the device and environmental changes, and to realize the optimization of the control of the device. The wi-fi wireless networking communication technology is chosen to transmit the real-time data acquired by the sensors to the web page. The electrical and electronic architecture composed of the two combined with each other is carried to the intelligent control platform to realize the functions of sensing, positioning, planning and decision-making of the equipment platform. The study shows that: the algorithm selected in this paper can reach the target speed of the motor within 0.2s in the process of no-load and loaded operation, and the time required for balancing to the load torque is significantly reduced compared with the comparison algorithm. In this paper, the maximum throughput and CPU occupancy of the domain controller + wireless sensor architecture are lower than that of the traditional distributed architecture. And the platform constructed accordingly has no packet loss when the number of packets sent is less than 10000, and the average communication delay is between 0.65 and 1.2ms, which meets the requirements of vehicle wireless control and communication. Through the domain controller based on adaptive control algorithm to regulate the vehicle speed in real time, to ensure the safety distance between the rear vehicle and the front vehicle.

Learning path optimization aims to generate and optimize a knowledge learning sequence for learners that best meets their knowledge needs. This study focuses on the important role of online learner behavior in personalized path planning. By constructing a knowledge point difficulty model and a learning behavior prediction model based on online learning behavior, together with a user-based collaborative filtering recommendation algorithm, a personalized learning path is proposed comprehensively. The MOOC websites “College English 1” and “Xuedang Online” are selected as sample data to analyze the online learning behavior of English learners and verify the learning effect of the learning path proposed in the article through the change of students’ online time. The personalized teaching model based on the learning path is investigated in practice by taking the college English course in school A as an example. Compared with the traditional teaching mode, the optimized learning path shows a significant difference of 0.01% in the dimensions of learners’ “knowledge and skills”, “process and method” and “affective attitude”. The mean values of the optimized blended teaching mode are 4.12, 4.33 and 4.07 respectively, which are all better than the traditional teaching mode. It shows that the English learning path proposed in this paper is conducive to enhancing students’ personalized learning needs and provides a reference for promoting the effective implementation of personalized learning in the information technology environment.

As the key driving force to promote the development of new quality productivity, the internal logic of the integration of production and education is to provide core support for the development of new quality productivity by training high-quality workers, providing high-quality labor elements and creating an efficient innovation platform. However, at present, the integration of middle and teaching in undergraduate education faces challenges such as “school hot and enterprise cold”, school-enterprise cooperation obstacles, and imperfect mechanism. This paper analyzes the current situation of the integration of production and education in undergraduate education, constructs the corresponding mathematical model. And uses genetic algorithm to solve the optimization objectives of curriculum design and teaching resource allocation under the integration of production and education, include the incorporation of enterprise elements, such as the proportion of enterprise practice courses, enterprise mentors, joint research and development data. Based on the above, the feasibility of GA optimization algorithm is tested from three perspectives: comparison of the same kind, practical application and student satisfaction. In order to effectively enable the development of new quality productivity, it is necessary to optimize the education major setting in accordance with industrial changes, deepen the learning situation and customize practical courses, deepen the school-enterprise cooperation and development platform, strengthen collaborative innovation, and improve the incentive mechanism, so as to form an effective connection between the education chain, the talent chain, the industrial chain and the innovation chain, and jointly promote the high-quality development of undergraduate education.

Teaching and correcting athletes’ techniques by analyzing and referring to the performance of professional tournament players can improve the teaching level and quality of wushu movements. In this paper, the performance of college students in UFC tournaments is taken as the research data, and the multilayer perceptron algorithm is used to process the images and carry out the global modeling of wushu fighting action images. The network coding design is used to improve the data transmission rate of the algorithm, and the activation function is used as the nonlinear expression method of the algorithm. The Tanh_Softsign activation function is improved to counteract the noise interference of the dataset images, in order to construct the multilayer perceptual machine algorithm and develop the learning of martial arts fighting action scores. After optimizing the learning of UFC martial arts action scores by this algorithm, this algorithm shows a high correlation between the performance scores of students and the professional teachers’ scores of an elective class of martial arts in a university with P>0.05, which indicates that the algorithm in this paper can accurately assess the students’ action performance.