School of Urban Construction, Hebei Normal University of Science and Technology, Qinhuangdao 066000, China.
School of Physical Education and Health, Hebei Normal University of Science and Technology, Qinhuangdao 066000, China.
J Environ Public Health. 2022 Sep 9;2022:7381483. doi: 10.1155/2022/7381483. eCollection 2022.
At present, the mental health problems of college students in China are on the rise. Many incentives lead to college students becoming a psychological vulnerable group, lacking the minimum "decompression ability" in the face of pressure. With the emergence of new media and the increasingly obvious fusion of new media and traditional media, the recognition algorithm of media fusion begins to enter people's vision, and multimedia fusion has gradually formed an irresistible development trend. Based on the media fusion recognition algorithm under the background of media fusion, this paper studies the model of college students' mental health education. In the process of comparing the accuracy of college students' mental health, the accuracy of this method is the highest, up to 99.25%, followed by the decision tree algorithm, up to 80.53%, and finally the ant colony algorithm, up to 75.25%. Therefore, this method is more conducive to the study of college students' mental health. Under the media fusion recognition algorithm, colleges and universities should give full play to the advantages of media fusion, broaden the path of mental health education, enhance the effectiveness of mental health education, improve the quality and efficiency of education, and guide the mental health growth of college students.
目前,中国大学生的心理健康问题呈上升趋势。许多诱因导致大学生成为心理弱势群体,面对压力缺乏最基本的“减压能力”。随着新媒体的出现和新媒体与传统媒体融合的日益明显,媒体融合的识别算法开始进入人们的视野,多媒体融合逐渐形成了一种不可阻挡的发展趋势。基于媒体融合背景下的媒体融合识别算法,本文研究了大学生心理健康教育模型。在比较大学生心理健康准确率的过程中,该方法的准确率最高,达到 99.25%,其次是决策树算法,达到 80.53%,最后是蚁群算法,达到 75.25%。因此,该方法更有利于研究大学生的心理健康。在媒体融合识别算法下,高校要充分发挥媒体融合优势,拓宽心理健康教育途径,增强心理健康教育实效性,提高教育质量和效益,引导大学生心理健康成长。