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논문 기본 정보

자료유형
학술저널
저자정보
Peng Zhang (Cangzhou Normal University) Wenjing Han (Handan University) Quanzhi Liu (Cangzhou Normal University)
저널정보
대한전자공학회 IEIE Transactions on Smart Processing & Computing IEIE Transactions on Smart Processing & Computing Vol.13 No.4
발행연도
2024.8
수록면
393 - 401 (9page)
DOI
10.5573/IEIESPC.2024.13.4.393

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초록· 키워드

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The mental health of college students is facing challenges because of the rapid changes in society. Anticipating these changes to enhance the emotional well-being of college students is crucial. This study devised a questionnaire focusing on pressure sources, such as employment and academic pressures. The mental health of college students was assessed using the SCL-90 scale, and data were collected as samples. A predictive model based on a back-propagation neural network (BPNN) was then constructed. The BPNN parameters were fine-tuned using the improved seagull optimization algorithm (ISOA), resulting in the ISOA-BPNN prediction model. The ISOA algorithm improved the BPNN prediction performance significantly compared to optimization algorithms, such as particle swarm optimization (PSO) and artificial bee colony (ABC), achieving an accuracy of 0.9762, an F1 value of 0.9834, and an area under the curve (AUC) of 0.9956. The ISOA-BPNN model demonstrated superior performance in predicting the mental health status of college students compared to prediction models, such as Logistic regression. These findings confirm the reliability of the ISOA-BPNN model developed in this study for predicting the mental health of college students and its potential applicability.

목차

Abstract
1. Introduction
2. Big Data Analysis of College Students’ Mental Health
3. Prediction Model based on BPNN
4. Results and Analysis
5. Discussion
6. Conclusion
References

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