Abstract
With the continuous advancement and development of information technology, the psychological problems of university students have attracted more and more social attention. Teachers should pay attention to the psychological problems of university students, actively strengthen psychological crisis pre-warning and intervention measures, and constantly eliminate psychological problems of students. In this paper, a prediction model of university students’ psychological mood fluctuation based on fuzzy neural network (FNN) is proposed, and the pre-alarm of university students’ psychological health status is completed through the cooperation among neurons such as psychological data collection and psychological well-being evaluation. Compared with the traditional psychological prediction algorithm, the accuracy of this algorithm has obvious advantages. Therefore, it is feasible to analyze the influence mechanism of external environmental impact on university students’ psychological and emotional fluctuations through this model. The impact of external environmental shocks on the psychological and emotional fluctuations of college students includes: an increase in uncertainty in life and a lack of psychological security; Increasing difficulty in employment and further education stimulates the generation of negative emotions; Some students have intensified family conflicts and amplified the negative impact of family relationships.
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Research on the Conduction and Influence Mechanism of External Environment Impact on University Students' Psychological and Emotional Fluctuations (A2021002).
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Luo, H. (2024). Research on the Influence Mechanism of External Environment Impact on University Students’ Psychological and Emotional Fluctuations Based on Deep Learning. In: Kountchev, R., Patnaik, S., Nakamatsu, K., Kountcheva, R. (eds) Proceedings of International Conference on Artificial Intelligence and Communication Technologies (ICAICT 2023). ICAICT 2023. Smart Innovation, Systems and Technologies, vol 369. Springer, Singapore. https://doi.org/10.1007/978-981-99-6956-2_2
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DOI: https://doi.org/10.1007/978-981-99-6956-2_2
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