Entrepreneurial role models are the forerunners on the path to entrepreneurship for college students, and they play a significant role in influencing college students’ entrepreneurship decisions. Entrepreneurship education in schools is an important tool for college students to develop entrepreneurial knowledge, ingenuity, and abilities. The main approach of building fuzzy systems is fuzzy integrated assessment, and it has a broad range of applications, including expert evaluation systems, quality control, performance assessment, weather forecasting, medical diagnosis, economic management, and psychological measurement. This research designs a fuzzy integrated evaluation system of university students’ entrepreneurial education using the environment, teaching process, and instructors’ team as the first-level indicators on the premise of defining the connotation of inventive and entrepreneurial skills. The article also uses the fuzzy integrated assessment method to conduct an empirical study and proposes countermeasures for the quality of innovative and entrepreneurial talents cultivation in terms of creating a good innovation environment in universities and encouraging students to actively participate in various innovative and entrepreneurial activities. The experimental results show that the half confidence of the fuzzy integrated assessment algorithm is 0.657, the retest confidence is 0.991, and the standard deviation of the α coefficient among all the test subjects is 0.683, which indicates that it has good confidence. Therefore, the fuzzy integrated assessment method of college students’ entrepreneurial education in this study is a combination of quantitative and qualitative methods, which expresses and processes the subjective judgment of human in quantitative form, minimizes the drawbacks brought by personal subjective judgment, and makes the evaluation results more credible.

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In recent years, with the development of Internet, Internet technology has swept the world and become a new round of scientific and technological revolution in the world economy. Network marketing has become the “darling” of marketing, with a multidimensional and multilevel marketing layout, which provides a carrier platform for the promotion of enterprise marketing strategy. The traditional network marketing mode is mainly in the form of advertising push, with pop-ups, screen overlays, top search rankings, loading videos, texts, and pictures. Nowadays, Internet technology and social media have promoted the development of community e-commerce models. Live delivery is a new sales model, which has promoted economic development. It has many advantages, such as interactivity, real-time, and transparency. Compared with the traditional e-commerce model, it is more suitable for the development requirements of the new era. Live delivery is a new sales model, which promotes economic development. This paper starts with the AdaBoost algorithm and marketing mode of STP and 4P marketing theory, in order to reduce the execution cost of marketing. In this way, it proves that using online marketing can not only reduce the cost but also improve the marketing effect. Through the new network marketing promotion mode and algorithm described in this paper, the cost can be reduced by 17%, and the promotion effect is remarkable.

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Soil aggregate stability and soil erodibility (k) are crucial indicators of soil quality that exhibit high sensitivity to changes in soil function. Therefore, it is of great significance to explore the quantitative relationship between these indicators and soil quality for effective ecosystem monitoring and assessment. In this study, soil samples were collected from eight altitude gradients in a karst mountainous area; we analyzed 11 soil physical, chemical, and biological properties, and assessed soil quality using the minimum data set (MDS) method. The results revealed that soil aggregate stability, bulk density (BD), pH, and fungal community diversity exhibited a unimodal altitudinal pattern, whereas the soil organic carbon (SOC), total nitrogen (TN), and C:N ratio showed an increasing trend. Among the factors considered, SOC, BD, soil pH, mechanical composition, and fungal community diversity were found to explain the most variation in soil aggregate stability and soil erodibility (k). Principal component analysis (PCA) identified soil fungal community diversity, C:N ratio, coarse sand, and macro-aggregate (MA) content as highly weighted indicators for MDS. The integrated soil quality index (SQI) values, ranging from 0.30 to 0.62 across the eight altitude gradients, also exhibited a unimodal altitudinal pattern. The analysis indicated a significant linear relationship between the fractal dimension (D) and soil erodibility of the EPIC model (Kepic) with SQI, suggesting that D and Kepic can serve as alternative indicators for soil quality. These findings further enhance our understanding of the response of soil properties to altitude changes, and provide a novel method for assessing and monitoring soil quality in karst mountainous areas.