Izvorni znanstveni članak
https://doi.org/10.20532/cit.2023.1005727
Evaluation Model of the Mental Health Education Effectiveness Based on Deep Neural Networks
Junmei Luo
; School of Marxism, Sichuan University, Chengdu, China
Shuchao Deng
; School of Computer Science, Sichuan University, Chengdu, China
Sažetak
This research develops a deep neural network model called DNN-MHE to evaluate mental health education effects. A questionnaire survey collected data on 916 students' mental health knowledge, attitudes, and behaviors. DNN-MHE uses five fully connected layers to predict mental health metrics. Experiments demonstrate that DNN-MHE achieves 99.46% accuracy, outperforming RNN, CNN, and shallow MLP models. Ablation studies validate the impact of training iterations, number of neurons, and number of data samples on performance. Overall, DNN-MHE enables accurate and efficient analysis of mental health education with practical implications for improving university programs.
Ključne riječi
deep neural network, mental health education, neuron numbers
Hrčak ID:
313207
URI
Datum izdavanja:
8.1.2024.
Posjeta: 109 *