基于神经网络的学生心理健康重要性及影响分析

Pinni Liu
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摘要

随着神经网络的迅速发展已广泛应用于各大研究领域,本文将神经网络的卷积层结构纳入到学生心理健康的重要性及影响因素中。为了分析大学生心理健康的影响因素,本文从神经网络的角度对不同学生的心理健康状况进行了分析。首先,提出了大学生心理健康的主要定义和概念,分析了大学生心理健康的评价和测量方法。其次,详细描述了神经网络的相关结构和两种不同的神经网络模型算法,并提出了神经网络的前向传播和后向传播算法(为后续通过神经网络进行数据研究提供支持)。最后,运用神经网络相关函数分析当代大学生心理健康的影响因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysis of the Importance and Influence of Student Mental Health Based on Neural Networks
With the rapid development of neural network has been widely used in major research areas, this paper will neural network convolution layer structure into the importance of students' mental health and influencing factors. In order to analyze the influencing factors of students' mental health, this paper analyzes the mental health status of different students from the perspective of neural network. Firstly, the main definitions and concepts of students' mental health are put forward, and the methods of evaluating and measuring mental health are analyzed. Secondly, the related structure of neural network and two different neural network model algorithms are described in detail, and the forward propagation and backward propagation algorithms of neural network are proposed (which provide support for the data research through neural network later). Finally, the correlation function of neural network is used to analyze the influencing factors of contemporary students' mental health.
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