College music teaching and ideological and political education integration mode based on deep learning

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Journal of Intelligent Systems Pub Date : 2022-01-01 DOI:10.1515/jisys-2022-0031

Xiaoshu Wang, Su-hua Zhao, Jingwen Liu, Liyan Wang

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引用次数: 4

Abstract

Abstract In order to highlight the role of music teaching in the teaching of ideological and political courses, this study puts forward research on the integration of music teaching and ideological and political teaching. This study analyzes the promotion and necessity of college music teaching to ideological and political work, constructs a fusion model of college music teaching and ideological and political work, introduces deep learning methods, and weakens the influence of errors in the data of college music teaching and ideological and political work. This study also optimized the integration mode of college music teaching and ideological and political work and realized the model research of college music teaching and ideological and political work. The experimental results show that the resource output amplitude controlled by the deep learning method has the best stability, and there is no large amplitude fluctuation during the experiment. The output amplitude and control time of the fusion resource are guaranteed and the fusion path of music teaching and ideological and political education is clearer. The maximum control time of the fusion resource of this method is 23.55 ms.

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基于深度学习的高校音乐教学与思想政治教育一体化模式

摘要为了突出音乐教学在思想政治课教学中的作用，本研究提出了音乐教学与思想政治课教学整合的研究。分析了高校音乐教学对思想政治工作的促进作用和必要性，构建了高校音乐教学与思想政治工作的融合模式，引入深度学习方法，弱化了高校音乐教学与思想政治工作数据误差的影响。优化了高校音乐教学与思想政治工作的整合模式，实现了高校音乐教学与思想政治工作的模式研究。实验结果表明，深度学习方法控制的资源输出幅度具有最好的稳定性，实验过程中没有出现较大的幅度波动。融合资源的输出幅度和控制时间得到保证，音乐教学与思想政治教育的融合路径更加清晰。该方法对融合资源的最大控制时间为23.55 ms。

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来源期刊

Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

5.90

自引率

3.30%

发文量

审稿时长

51 weeks

期刊介绍： The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.