Ethnic music heritage in college piano teaching based on adaptive differential evolutionary algorithm
Publicado en línea: 21 oct 2023
Recibido: 22 ene 2023
Aceptado: 01 may 2023
DOI: https://doi.org/10.2478/amns.2023.2.00735
Palabras clave
© 2023 Shanshan Shi, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
This paper uses an adaptive differential evolution algorithm to handle multiple conflicting optimization objectives by randomly generating uniformly distributed values corresponding to the upper and lower bounds so that the variance vectors are crossed over. A diversity metric measures the degree of uniformity of distribution between solutions, using a pre-given interval of static variables and introducing a special differential mutation pattern for iteration. The highest value of the adaptive differential evolution algorithm piano performance time was 13.5 s, and the highest value of the teaching quality situation was 0.864. With the adaptive differential evolution algorithm, the piano teaching content can be enhanced, students' interest in folk music can be nurtured, and folk music can be inherited and promoted.