College music teaching and ideological and political education integration mode based on deep learning
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 ideologica...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2022-04-01
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| Series: | Journal of Intelligent Systems |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/jisys-2022-0031 |
| _version_ | 1811202983991443456 |
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| author | Wang Xiaoshu Zhao Suhua Liu Jingwen Wang Liyan |
| author_facet | Wang Xiaoshu Zhao Suhua Liu Jingwen Wang Liyan |
| author_sort | Wang Xiaoshu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T02:48:12Z |
| format | Article |
| id | doaj.art-0cb1295184934710b4edb4660d8cf526 |
| institution | Directory Open Access Journal |
| issn | 2191-026X |
| language | English |
| last_indexed | 2024-04-12T02:48:12Z |
| publishDate | 2022-04-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Journal of Intelligent Systems |
| spelling | doaj.art-0cb1295184934710b4edb4660d8cf5262022-12-22T03:51:06ZengDe GruyterJournal of Intelligent Systems2191-026X2022-04-0131146647610.1515/jisys-2022-0031College music teaching and ideological and political education integration mode based on deep learningWang Xiaoshu0Zhao Suhua1Liu Jingwen2Wang Liyan3College of Continuing Education, Xuanhua Vocational College of Science & Technology, Zhangjiakou 075100, ChinaDean’s Office, Xuanhua Vocational College of Science & Technology, Zhangjiakou 075100, ChinaCollege of Pre-primary Education, Xuanhua Vocational College of Science & Technology, Zhangjiakou 075100, ChinaCollege of Pre-primary Education, Xuanhua Vocational College of Science & Technology, Zhangjiakou 075100, ChinaIn 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.https://doi.org/10.1515/jisys-2022-0031deep learningcollege musicideological and political educationmathematical modeling |
| spellingShingle | Wang Xiaoshu Zhao Suhua Liu Jingwen Wang Liyan College music teaching and ideological and political education integration mode based on deep learning Journal of Intelligent Systems deep learning college music ideological and political education mathematical modeling |
| title | College music teaching and ideological and political education integration mode based on deep learning |
| title_full | College music teaching and ideological and political education integration mode based on deep learning |
| title_fullStr | College music teaching and ideological and political education integration mode based on deep learning |
| title_full_unstemmed | College music teaching and ideological and political education integration mode based on deep learning |
| title_short | College music teaching and ideological and political education integration mode based on deep learning |
| title_sort | college music teaching and ideological and political education integration mode based on deep learning |
| topic | deep learning college music ideological and political education mathematical modeling |
| url | https://doi.org/10.1515/jisys-2022-0031 |
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