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

<p>To solve the problem of low teaching efficiency in the traditional music course online assistant teaching system, the author proposes a music teaching technology analysis method based on a data mining model. The author proposes a music education model based on the RBF algorithm, which will help improve students’ exploration skills and play an important role for teachers. Through learning and teaching, students can become the center of learning and promote their interest and knowledge in music education. Firstly, the research status of intelligent interactive music learning is analyzed, and then the creation of a neuron model and RBF algorithm using intelligent technology, the definition of music learning methods, and the creation of an independent learning platform are discussed. Select an existing manual for comparative testing. The experimental results show that the training performance of the proposed method exceeds 90%. Although the training performance of both systems is improving, the demonstration of the planning process is very high, and there are some opportunities. Conclusion: Intelligent machines play a great role in students’ music learning, providing better learning opportunities, and providing useful aspects for educational research.</p>
</abstract>

To solve the problem of low teaching efficiency in the traditional music course online assistant teaching system, the author proposes a music teaching technology analysis method based on a data mining model. The author proposes a music education model based on the RBF algorithm, which will help improve students’ exploration skills and play an important role for teachers. Through learning and teaching, students can become the center of learning and promote their interest and knowledge in music education. Firstly, the research status of intelligent interactive music learning is analyzed, and then the creation of a neuron model and RBF algorithm using intelligent technology, the definition of music learning methods, and the creation of an independent learning platform are discussed. Select an existing manual for comparative testing. The experimental results show that the training performance of the proposed method exceeds 90%. Although the training performance of both systems is improving, the demonstration of the planning process is very high, and there are some opportunities. Conclusion: Intelligent machines play a great role in students’ music learning, providing better learning opportunities, and providing useful aspects for educational research.

Analysis of music teaching technology based on a data mining model

Applied Mathematics and Nonlinear Sciences

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

{"article-title":"Analysis of music teaching technology based on a data mining model"}

To solve the problem of low teaching efficiency in the traditional music course online assistant teaching system, the author proposes a music teaching...

Analysis of music teaching technology based on a data mining model

Data publikacji: 07 lip 2023

Zakres stron: 3013 - 3022

Otrzymano: 21 sie 2022

Przyjęty: 13 sty 2023

DOI: https://doi.org/10.2478/amns.2023.2.00017

Słowa kluczowe
Music curriculum model, cloud computing, data mining, architecture, interactive system, RBF algorithm

© 2023 Yi Liu, published by Sciendo

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

Analysis of music teaching technology based on a data mining model

Data publikacji: 07 lip 2023

Zakres stron: 3013 - 3022

Otrzymano: 21 sie 2022

Przyjęty: 13 sty 2023

DOI: https://doi.org/10.2478/amns.2023.2.00017

Słowa kluczoweMusic curriculum model, cloud computing, data mining, architecture, interactive system, RBF algorithm

© 2023 Yi Liu, published by Sciendo

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

Słowa kluczowe
Music curriculum model, cloud computing, data mining, architecture, interactive system, RBF algorithm