Back to Search Start Over

The Acceptance Status of Traditional Moral Culture in Colleges and Universities Using Convolutional Neural Network.

Authors :
Liu, Bingduan
Source :
Scientific Programming. 2/24/2022, p1-12. 12p.
Publication Year :
2022

Abstract

In today's world, competition among countries is not just a contest of hard force, but also a contest of soft power. China has a five-thousand-year-old history and civilization, with a strong traditional moral culture at its core. The university stage is an important time for college students to develop their worldview, outlook on life, and values. In this context, excellent traditional and moral culture education plays an important role and significance in their development. College students are the country's future builders and an important force to inherit China's excellent moral culture. The rapid development of the modern Internet era has made the channels for college students to understand and accept the cultures of various countries more and more diverse and convenient. Actively borrowing their essence can help promote the development of Chinese culture, but we must also pay attention to active defense and resistance against the dregs of culture. This paper discusses the current situation and problems of the acceptance status of excellent traditional moral culture among college students and analyses the factors that restrict the acceptance of excellent traditional moral culture among college students to conduct a large-scale study on the acceptance status of traditional moral culture in colleges and universities. A model based on convolutional neural networks is suggested for predicting college students' embrace of traditional moral values. By learning and describing their activities and preferences on the Internet, the model assesses and creates college students' acceptance status for conventional moral culture. Extensive tests indicate that the suggested technique can successfully assess college students' acceptance status for traditional moral culture, and the model's superior performance is supported by test results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10589244
Database :
Academic Search Index
Journal :
Scientific Programming
Publication Type :
Academic Journal
Accession number :
155430250
Full Text :
https://doi.org/10.1155/2022/7868591