Research article

SIMULATION TRAINING METHOD OF FOLK MUSIC CONDUCTOR BASED ON DYNAMIC EVOLUTIONARY CLUSTERING ALGORITHM

Jiajia Li

Online First: December 22, 2022


The existing folk music conductor simulation training methods have the problem of imperfect data stream storage structure, resulting in low clustering accuracy. A folk music conductor simulation training method based on dynamic evolutionary clustering algorithm is designed. Divide the curriculum level, identify the value orientation of talent training curriculum, obtain the command characteristics of folk music, regulate the sound facilities, take the attributes of sample points as the judgment standard, use the dynamic evolutionary clustering algorithm to build the data stream storage structure, calculate the sample similarity, and design the simulation training mode of folk music talents. Experimental results: the average clustering accuracy of the folk music conductor simulation training method and the other two folk music conductor simulation training methods is 59.542%, 51.759% and 51.291%, which proves that the training method integrating dynamic evolutionary clustering algorithm has better performance.

Keywords

dynamic evolutionary clustering algorithm; folk music conductor; training courses; training methods; data flow; storage structure;