Student Behavior Prediction of Mental Health Based on Two-Stream Informer Network
Students’ mental health has always been the focus of social attention, and mental health prediction can be regarded as a time-series classification task. In this paper, an informer network based on a two-stream structure (TSIN) is proposed to calculate the interdependence between students’ behaviors...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/13/4/2371 |
| _version_ | 1827758817470840832 |
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| author | Jieming Xu Xuefeng Ding Hanyu Ke Cong Xu Hanlun Zhang |
| author_facet | Jieming Xu Xuefeng Ding Hanyu Ke Cong Xu Hanlun Zhang |
| author_sort | Jieming Xu |
| collection | DOAJ |
| description | Students’ mental health has always been the focus of social attention, and mental health prediction can be regarded as a time-series classification task. In this paper, an informer network based on a two-stream structure (TSIN) is proposed to calculate the interdependence between students’ behaviors and the trend of time cycle, and the intermediate features are integrated layer by layer to realize the prediction of mental health by a gating mechanism. Through experiments on a real campus environment dataset (STU) and an open dataset (MTS), it is verified that the proposed algorithm can obtain higher accuracy than existing methods. |
| first_indexed | 2024-03-11T09:11:51Z |
| format | Article |
| id | doaj.art-4142d237804e4fe7808b27a54a0bcf93 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-11T09:11:51Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4142d237804e4fe7808b27a54a0bcf932023-11-16T18:54:47ZengMDPI AGApplied Sciences2076-34172023-02-01134237110.3390/app13042371Student Behavior Prediction of Mental Health Based on Two-Stream Informer NetworkJieming Xu0Xuefeng Ding1Hanyu Ke2Cong Xu3Hanlun Zhang4College of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaCollege of Computer Science, Sichuan University, Chengdu 610065, ChinaStudents’ mental health has always been the focus of social attention, and mental health prediction can be regarded as a time-series classification task. In this paper, an informer network based on a two-stream structure (TSIN) is proposed to calculate the interdependence between students’ behaviors and the trend of time cycle, and the intermediate features are integrated layer by layer to realize the prediction of mental health by a gating mechanism. Through experiments on a real campus environment dataset (STU) and an open dataset (MTS), it is verified that the proposed algorithm can obtain higher accuracy than existing methods.https://www.mdpi.com/2076-3417/13/4/2371two-stream informerstudent behavior analysistime-series classificationintermediate feature fusion |
| spellingShingle | Jieming Xu Xuefeng Ding Hanyu Ke Cong Xu Hanlun Zhang Student Behavior Prediction of Mental Health Based on Two-Stream Informer Network Applied Sciences two-stream informer student behavior analysis time-series classification intermediate feature fusion |
| title | Student Behavior Prediction of Mental Health Based on Two-Stream Informer Network |
| title_full | Student Behavior Prediction of Mental Health Based on Two-Stream Informer Network |
| title_fullStr | Student Behavior Prediction of Mental Health Based on Two-Stream Informer Network |
| title_full_unstemmed | Student Behavior Prediction of Mental Health Based on Two-Stream Informer Network |
| title_short | Student Behavior Prediction of Mental Health Based on Two-Stream Informer Network |
| title_sort | student behavior prediction of mental health based on two stream informer network |
| topic | two-stream informer student behavior analysis time-series classification intermediate feature fusion |
| url | https://www.mdpi.com/2076-3417/13/4/2371 |
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