基于层次聚类算法的促进大学生心理健康的艺术疗法

IF 0.7 4区 工程技术 Q4 ENGINEERING, MARINE
J Y Zheng
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引用次数: 0

摘要

艺术疗法是一种利用艺术创作过程来改善心理、情感和生理健康的治疗方法。艺术疗法是一种表达性疗法,它利用艺术创作过程来改善精神、情绪和心理健康。它为个人提供了一种非语言的自我表达和探索渠道,使他们能够在安全和支持性的环境中交流和处理自己的思想、情感和经历。本文提出了一种高效的加权分层聚类深度神经网络(WH-CDNN)来促进大学生的心理健康。所提出的 WH-CDNN 模型提取了艺术疗法的特征,以促进学生的心理健康。分析所考虑的特征包括色调、纹理和促进学生心理健康评估的疗法。与加权模型相关的特征是为大学生心理健康评估而计算的。WH-CDNN 模型的特征使用分层聚类模型计算基于心理健康评估的艺术治疗特征。该研究基于对 10 个特征的估计和心理健康评估的 5 个聚类的考虑。实验分析结果表明,所提出的 WH-CDNN 模型在学生艺术治疗后的心理健康评估中取得了显著的改善。 通过模拟和分析,该研究证明了艺术疗法在改善心理健康结果方面的有效性,观察到治疗后焦虑和抑郁水平显著降低。此外,WH-CDNN 模型还能准确预测学生的心理健康状况,并评估艺术疗法干预措施的效果。研究结果凸显了将先进的计算技术与艺术疗法相结合的潜力,以支持学生的身心健康,并为教育环境中有针对性的心理健康干预措施提供信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Art Therapy to Promote College Students’ Mental Health Based on a Hierarchical Clustering Algorithm
Art therapy is a therapeutic approach that utilizes the creative process of making art to improve mental, emotional, and physical well-being. Art therapy is a form of expressive therapy that utilizes the creative process of making art to improve mental, emotional, and psychological well-being. It provides individuals with a non-verbal outlet for self-expression and exploration, allowing them to communicate and process their thoughts, feelings, and experiences in a safe and supportive environment. This paper proposed an efficient Weighted Hierarchical Clustering Deep Neural Network (WH-CDNN) to promote the mental health of college students. The proposed WH-CDNN model extracts the features of the art therapy to promote the mental health of students. The features considered for the analysis are color palette, texture, and therapy for the promotion of mental health assessment of students. The features associated with the weighted model are computed for the college student mental health assessment. The features with the WH-CDNN model use the hierarchical clustering model for the computation of the features in art therapy based on the assessment of mental health. The examination is based on the consideration of 10 features for the estimation with the 5 clusters for the evaluation of the mental health assessment. Experimental analysis of the results demonstrated that the proposed WH-CDNN model achieves significant improvement in the after the art therapy of the students with the mental health assessment.  Through simulation and analysis, the study demonstrates the effectiveness of art therapy in improving mental health outcomes, with significant reductions observed in anxiety and depression levels post-therapy. Moreover, the WH-CDNN model accurately predicts students' mental health states and evaluates the efficacy of art therapy interventions. The findings highlight the potential of integrating advanced computational techniques with art therapy to support student well-being and inform targeted mental health interventions in educational settings.
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来源期刊
CiteScore
1.20
自引率
0.00%
发文量
18
审稿时长
>12 weeks
期刊介绍: The International Journal of Maritime Engineering (IJME) provides a forum for the reporting and discussion on technical and scientific issues associated with the design and construction of commercial marine vessels . Contributions in the form of papers and notes, together with discussion on published papers are welcomed.
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