Analysis of Educational Mental Health and Emotion Based on Deep Learning and Computational Intelligence Optimization

• DOI: 10.3389/fpsyg.2022.898609
• Publication Date: 2022-06-20T16:07:38Z
• Authors: Junli Liu; Haoyuan Wang
• Keywords: Sadness

Understanding students’ psychological pressure and bad emotional reaction can solve problems as soon possible avoid affecting normal study life. With the improvement of global scientific technological strength, step-by-step in-depth research on deep learning computational intelligence optimization. Now, we have enough conditions to build a data set for field education, mental health stress detection model with analysis function. In addition, variety experimental methods are used comparison, which shows superior performance in practical application scenarios. The results show that: (1) constructed is reasonable. Psychological test that tested college students good no positive performance. Schools need pay special attention obsessive–compulsive disorder interpersonal sensitivity, average values both indicators higher than 0.9. (2) For optimization ant colony algorithm (ACO) intelligence, stability execution time obviously those other algorithms. This has obvious advantages after using this algorithm. (3) Using loss function value measure difference between simulated emotion real value. most tests less 3%; accuracy sadness fear about 7%. Although final prove feasibility method, there still some shortcomings be optimized.