<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In this paper, the fusion teaching model was constructed, and the clustering of music elements was statistically calculated by calculating the intra-class distance of music elements. The feature vector of big data clustering is extracted, the traditional music element data is partitioned using linear FM signal, and the spatial matrix of traditional music element data is obtained after initializing the clustering center. To form the information flow model of big data time series, the phase space reconstruction analysis method is used to process piano data in nonlinear mapping. To achieve the objective function after clustering, adjust the weights within the fitness function, and then output the optimal program of the integrated teaching model. The results show that the post-test scores of students in the experimental group are higher than those of students in the control group, and the scores of tuning and composition have been improved by 2 and 2.5 points to reach the full score of 10 compared with those of the control group, which demonstrates the validity and feasibility of the fusion teaching mode of traditional music elements and college piano.</p>
</abstract>

In this paper, the fusion teaching model was constructed, and the clustering of music elements was statistically calculated by calculating the intra-class distance of music elements. The feature vector of big data clustering is extracted, the traditional music element data is partitioned using linear FM signal, and the spatial matrix of traditional music element data is obtained after initializing the clustering center. To form the information flow model of big data time series, the phase space reconstruction analysis method is used to process piano data in nonlinear mapping. To achieve the objective function after clustering, adjust the weights within the fitness function, and then output the optimal program of the integrated teaching model. The results show that the post-test scores of students in the experimental group are higher than those of students in the control group, and the scores of tuning and composition have been improved by 2 and 2.5 points to reach the full score of 10 compared with those of the control group, which demonstrates the validity and feasibility of the fusion teaching mode of traditional music elements and college piano.

Analysis of the Integration Teaching Mode of Traditional Music Elements and College Piano under the View of Big Data

Sichuan University of Science & Engineering

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

In this paper, the fusion teaching model was constructed, and the clustering of music elements was statistically calculated by calculating the intra-class...

Analysis of the Integration Teaching Mode of Traditional Music Elements and College Piano under the View of Big Data

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 26. Dez. 2023

Akzeptiert: 05. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0307

Schlüsselwörter
Traditional music elements, Intraclass distance, Feature vector, Data clustering, Phase space reconstruction

© 2024 Dongming Hu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Analysis of the Integration Teaching Mode of Traditional Music Elements and College Piano under the View of Big Data

Online veröffentlicht: 31. Jan. 2024

Seitenbereich: -

Eingereicht: 26. Dez. 2023

Akzeptiert: 05. Jan. 2024

DOI: https://doi.org/10.2478/amns-2024-0307

SchlüsselwörterTraditional music elements, Intraclass distance, Feature vector, Data clustering, Phase space reconstruction

© 2024 Dongming Hu et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
Traditional music elements, Intraclass distance, Feature vector, Data clustering, Phase space reconstruction