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Music Teaching Management and Music Culture Communication Environment Based on Ergonomics
Music education has a relationship that is mutually restraining and interdependent. The necessity of spreading music culture offers music education social relevance and existential value in the history of music culture's growth, and the method of spreading music culture—music education—injects...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9492405/ https://www.ncbi.nlm.nih.gov/pubmed/36159769 http://dx.doi.org/10.1155/2022/4186092 |
Sumario: | Music education has a relationship that is mutually restraining and interdependent. The necessity of spreading music culture offers music education social relevance and existential value in the history of music culture's growth, and the method of spreading music culture—music education—injects strength and life into the development of music culture. Music pedagogy is constrained by the evolution of music culture as a whole. In terms of music pedagogy, traditional culture and their peculiarities or qualities will have an impact on the creation of the curriculum content system, which is also the main topic of music teaching management. By using anthropometry, physiological and psychological measurement, etc. with the human body as the main body, ergonomics is the study of the reasonable coordination between the structure and function of the human body, psychology, mechanics, and music teaching methods in order to satisfy people's physical and mental activities and achieve the best use efficiency. The focus should be on comfort, great performance, safety, and health. In order to create a model for evaluating the quality of music instruction, a back propagation neural network (BPNN) is optimised in this paper using an adaptive mutation genetic algorithm. According to the research, our approach outperforms the BPNN model optimised using conventional evolutionary algorithm by 20.21%. The convergence pace is 80.11% faster than the convergence speed of a conventional genetic algorithm. The comparative result demonstrates that the BPNN teaching quality evaluation model with genetic algorithm optimization based on adaptive mutation can produce a more logical scientific evaluation result for the quality of music instruction. |
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