Affiliation:
1. School of Traffic and Transportation, Northeast Forestry University, Haerbin 150000, China
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.
Subject
Computer Science Applications,Software
Cited by
2 articles.
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1. College Students' Psychological Prediction Algorithm Based on Internet Big Data Mining;2022 Second International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE);2022-12-16
2. Construction of Applied Undergraduate Course Evaluation System Based on BP Neural Network;Mobile Information Systems;2022-06-22