Prediction Method of College Students’ Psychological Pressure Based on Deep Neural Network

Abstract

Aiming at the problems of low prediction accuracy and efficiency and poor prediction effect in the current psychological pressure prediction methods, a psychological pressure prediction method for college students based on deep neural network is proposed. The structure and algorithm of depth neural network and gray theory model are analyzed. Using the deep neural network, this paper establishes the sample set data of college students’ psychological pressure prediction and constructs the college students’ psychological pressure prediction model combined with the deep neural network algorithm of gray theory. The physical network information model is formed through the relationship between neurons. According to the dynamic changes of college students’ psychological pressure in each neuron of the physical network, the prediction of college students’ psychological pressure is completed. The experimental results show that the proposed method is effective in predicting college students’ psychological pressure and can effectively improve the accuracy and efficiency of college students’ psychological pressure prediction.

Construction of Applied Undergraduate Course Evaluation System Based on BP Neural Network

“…e research object proposed in this paper, the application-oriented undergraduate colleges mainly refers to the general undergraduate colleges that exist in the statistics of the education department and typically exist between higher vocational colleges and subordinate comprehensive (research) colleges and universities, and most of them are under the management of local governments at all levels [16]. Compared with research-oriented undergraduate universities, application-oriented undergraduate universities mainly have the following connotative characteristics, as shown in Figure 5.…”

Psychological Crisis Prediction of Students Based on Network Behavior by Big Data Mining

“…In recent years, psychological problems of college students have increasingly attracted attention from various sectors of society [1][2][3]. In modern society, college students are faced with enormous pressure in their studies, daily life, and employment, which easily leads to their psychological problems [4][5][6][7][8][9]. At the same time, network behavior is an important way to reflect the psychological status of college students, because the rapid development of network technology has made their behavior increasingly diverse in the network.…”