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<p>To explore whether dance movement techniques in colleges and universities in the context of artificial intelligence can bring new developments in teaching methods in the field of teaching and whether its effectiveness can bring some new power to professional training. In this paper, the principle model of the dance technique movement system is used to calculate the correlation coefficient between music and dance movement characteristics. On this basis combined with a genetic algorithm to train the corresponding relationship of different music dance movements, through the accuracy of the corresponding relationship as an adaptation function, to obtain an optimal dance movement correspondence, to get the dance movement matching optimization objective function, and combined with ant colony theory to optimize the solution of this objective function, thus completing the optimization of dance movement matching in music choreography. The research results show that 83.5% of the students think that dance movement skills are relevant in teaching and can achieve the teaching effect faster and more effectively, and 70% of the students think that they have enough learning time to grasp the form of technical movements more skillfully. Therefore, it is very important to analyze the dance movement techniques in colleges and universities to teach and improve the quality of teaching.</p>
</abstract>

To explore whether dance movement techniques in colleges and universities in the context of artificial intelligence can bring new developments in teaching methods in the field of teaching and whether its effectiveness can bring some new power to professional training. In this paper, the principle model of the dance technique movement system is used to calculate the correlation coefficient between music and dance movement characteristics. On this basis combined with a genetic algorithm to train the corresponding relationship of different music dance movements, through the accuracy of the corresponding relationship as an adaptation function, to obtain an optimal dance movement correspondence, to get the dance movement matching optimization objective function, and combined with ant colony theory to optimize the solution of this objective function, thus completing the optimization of dance movement matching in music choreography. The research results show that 83.5% of the students think that dance movement skills are relevant in teaching and can achieve the teaching effect faster and more effectively, and 70% of the students think that they have enough learning time to grasp the form of technical movements more skillfully. Therefore, it is very important to analyze the dance movement techniques in colleges and universities to teach and improve the quality of teaching.

Research on the application of dance movement skill analysis in teaching in the context of artificial intelligence in universities

Applied Mathematics and Nonlinear Sciences

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

To explore whether dance movement techniques in colleges and universities in the context of artificial intelligence can bring new developments in teaching...

Research on the application of dance movement skill analysis in teaching in the context of artificial intelligence in universities

Pubblicato online: 30 giu 2023

Pagine: -

Ricevuto: 04 ago 2022

Accettato: 09 gen 2023

DOI: https://doi.org/10.2478/amns.2023.1.00482

Parole chiave
Artificial intelligence, Dance movement technique, Principle model, Ant colony theory, Function optimization

© 2023 Li Zhou, published by Sciendo

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

Research on the application of dance movement skill analysis in teaching in the context of artificial intelligence in universities

Pubblicato online: 30 giu 2023

Pagine: -

Ricevuto: 04 ago 2022

Accettato: 09 gen 2023

DOI: https://doi.org/10.2478/amns.2023.1.00482

Parole chiaveArtificial intelligence, Dance movement technique, Principle model, Ant colony theory, Function optimization

© 2023 Li Zhou, published by Sciendo

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

Parole chiave
Artificial intelligence, Dance movement technique, Principle model, Ant colony theory, Function optimization