Zheng Wanting
School of Clinical Medical Technology, Sichuan Vocational College of Health and Rehabilitation, Zigong, 643000 Sichuan, China.
Appl Bionics Biomech. 2022 Apr 18;2022:6394707. doi: 10.1155/2022/6394707. eCollection 2022.
With the rapid development of curricula, a large number of studies are emerging to assist in the development of curricula. But in an information society, in the face of rapid learning and increased life expectancy, students face the pressure not to forget; the mental health status as a result of our curricula is closely related to our learning. The research and application of the integration algorithm plays an important role in the analysis of the mental health education system. The purpose of this work is to study the application analysis algorithm in the students' context. This work applies the integration analysis algorithm to students' mental health analysis and identifies students' mental health problems using the integration analysis algorithm so that students are well informed and guided. Based on the system engineering method, using the data mining clustering method, a detailed analysis and research on the mental health of college students is done. In this work, a method of student behavior analysis and statistical tools are used to collect mental health data to find common features of different groups of students, in order to better visualize and investigate the mental health of these students on a scientific basis. The results of this study are as follows: a general analysis algorithm application on the analysis of students' mental health education system allows for an effective understanding of scientific data. FCM and FCM algorithms based on the density of information entropy characteristics were used to investigate the effect of mental health factors on the results of the study and the practicality of the algorithm used, which provided an effective method for the prevention of student mental problems. Assisting the school in formulating corresponding new methods of early prevention and intervention of college students' psychological disorders will create a good and healthy atmosphere for college students' study and life. The research results provide a reliable basis for managing and cultivating students.
随着课程的快速发展，大量研究不断涌现以助力课程开发。但在信息社会中，面对快速学习和预期寿命的增加，学生面临着不遗忘的压力；我们课程所导致的心理健康状况与我们的学习密切相关。整合算法的研究与应用在心理健康教育系统分析中发挥着重要作用。这项工作的目的是研究学生背景下的应用分析算法。这项工作将整合分析算法应用于学生心理健康分析，并使用整合分析算法识别学生的心理健康问题，以便让学生充分了解并得到指导。基于系统工程方法，运用数据挖掘聚类方法，对大学生心理健康进行了详细的分析与研究。在这项工作中，采用学生行为分析方法和统计工具来收集心理健康数据，以找出不同学生群体的共同特征，从而在科学基础上更好地可视化并研究这些学生的心理健康状况。本研究结果如下：在学生心理健康教育系统分析中应用通用分析算法能够有效理解科学数据。使用基于信息熵特征密度的模糊C均值（FCM）算法和FCM算法来研究心理健康因素对研究结果的影响以及所用算法的实用性，这为预防学生心理问题提供了一种有效方法。协助学校制定相应的大学生心理障碍早期预防和干预新方法，将为大学生的学习和生活营造良好健康的氛围。研究结果为管理和培养学生提供了可靠依据。
