Improved Fuzzy Algorithm for College Students’ Academic Early Warning

Abstract

The existing fuzzy clustering algorithms are mostly fuzzy comprehensive evaluation algorithms based on specific elements, but the main problem of such fuzzy algorithms is the lack of overall research on the responsible individuals and the lack of hierarchy in the algorithms. It is suitable for data mining of academic early warning systems. Therefore, an improved fuzzy algorithm based on fuzzy performance evaluation based on composite elements is proposed, and it is applied to the performance evaluation system to solve the complex problems in performance evaluation. In the process of building smart campuses in colleges and universities, academic prewarning, as the main part of smart campuses, mainly uses data mining technology to ensure students complete their studies smoothly and at the same time provides certain decision-making support for colleges and universities. Based on the research topic of the relevant departments of a certain school, this paper aims to build an academic early warning system suitable for the school to ensure that students can successfully complete their studies. The main research contents are divided into two parts: “study early warning model research” and “design and implementation of an academic early warning system.” Through analysis and experiments, it is proved that the model evaluation effect based on the algorithm improvement is the best, with recall reaching 85%, precision reaching 78.96%, and AUC reaching 80.25%.

Study on Employee Performance Evaluation Based on Adaptive Feature Selection Fuzzy Algorithm

“…Taking the amount of editing of the employee performance management file information document by each person in the process of employee performance management file information processing as a rigid indicator, it is calculated that each office employee receives the employee performance management file information from the employee performance management file information in the process of employee performance management file information flow [41,42]. e amount of editing between two employee performance management file information versions (that is, the number of modified characters in the document) for information forwarding the statistics of the editing volume of performance management file information is used as a quantitative reference index in the quantitative calculation of performance evaluation [43,44].…”

Academic Early Warning Model for Students Based on Big Data Analysis

“…Experiments showed that the SVM early warning model based on improved FOA was superior to the traditional SVM model, decision tree and random forest in accuracy. Chen [15] proposed an improved fuzzy algorithm, based on fuzzy performance evaluation of composite elements, and applied it to a performance evaluation system to solve complex problems in performance evaluation. In the process of building smart campus in universities, academic early warning, as a main component of smart campus, mainly aimed to ensure that students successfully completed their studies using data mining technology, and provided certain decision-making support for universities.…”