Study on Deep Learning Political Culture Communication System in Universities under the Perspective of Postmodern Media

Yanjun Luo, J. Chen, Shuhui Ren, Lan Luo, Tianlin Chen
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Abstract

with the development of industrialization and computer science and technology, people more and more attention to the intelligent industrial, big data applications in industry by leaps and bounds, artificial intelligence in various fields show their unique style. In this paper after the modern media from the perspective of Ideological and political culture to establish research study of artificial intelligence network based on the depth of political culture in universities, construct the perspective of postmodern media dissemination system. This paper is based on the MATLAB platform, constructing artificial intelligence after modern media from the perspective of political culture communication system based on its operation is simple, does not require advanced programming background. Based on probabilistic neural network, the colleges and universities from the perspective of modern media thought political and cultural communication system construction, and validation is based on probabilistic neural network artificial intelligence forecasting has good convergence and the ability of fault tolerance and data processing ability.
后现代传媒视域下高校深度学习政治文化传播系统研究
随着工业化和计算机科学技术的发展,智能工业越来越受到人们的重视,大数据在工业中的应用突飞猛进,人工智能在各个领域展现出自己独特的风采。本文从现代传媒之后的思想政治文化视角建立基于人工智能网络的高校政治文化深度研究,构建了后现代传媒视角下的传播体系。本文基于MATLAB平台,构建基于人工智能后现代媒体视角的政治文化传播系统,其操作简单,不需要高级编程背景。基于概率神经网络,从高校现代传媒的角度构建思想政治文化传播体系,并验证基于概率神经网络的人工智能预测具有良好的收敛性和容错能力以及数据处理能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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