We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
An Abnormal Behavior Detection Method Leveraging Multi-modal Data Fusion and Deep Mining.
- Authors
Xinyu Tian; Qinghe Zheng; Nan Jiang
- Abstract
At present, the increasingly prominent mental health problems of college students have gradually become the focus of the society, universities and families. According to the current situation and challenges of mental health work of college students, we put forward the idea of constructing an early warning platform for college students' psychological crisis based on deep neural networks. The purpose of constructing this platform is to comprehensively improve the psychological health of college students and to purposefully prevent and intervene the psychological crisis. In this paper, we focus on describing the structure, composition of proposed platform and functions of each module, and then give a specific framework, training and testing scheme for the core part of the platform, which is the neural network model for real-time monitoring and analysis of students' mental health. Finally, we demonstrate the effectiveness of the deep neural network for analyzing behavior patterns through simulation experiments on the generated data set.
- Subjects
MULTISENSOR data fusion; DATA fusion (Statistics); ARTIFICIAL neural networks; STUDENT health; MENTAL health of students; CRISIS communication; MENTAL work; CRISIS management
- Publication
IAENG International Journal of Applied Mathematics, 2021, Vol 51, Issue 1, p92
- ISSN
1992-9978
- Publication type
Article