Optimization of local ethnic music teaching transmission path based on logistic regression model

Abstract

Abstract To be able to better develop local folk music and traditional culture, this paper proposes the optimization of local folk music teaching and transmission paths. Analyze the musical styles taught in colleges and universities, learn that ethnic music with a strong national culture is not asked for, build a more comprehensive and three-dimensional system of musical knowledge, master the cultural connotations of ethnic music, strengthen the understanding of their own group culture, and lay the foundation for survival and development in a multicultural society. According to single or multiple continuous or discrete analysis of folk music teaching transmission paths, the state variables of the path optimization process are set to ensure that the growth rate coefficient of the teaching transmission path is positive and the growth rate of teaching is positive. Combining the amount of teaching demand for local ethnic music, the inflection point of the path curve is substituted into the transmission path to obtain the path state variable values. Using the fruit fly optimization algorithm to strengthen the Logistic model, the individual flight distance and direction of fruit flies are preset, and the distance value between the fruit fly position and the origin is calculated to locate toward the target position with visual advantage, and finally the music teaching transmission path optimization is realized. The analysis results show that the logistic model combined with the FOA algorithm has a significantly higher test rate both for subsamples and full samples, and the value of 0.45 is closer to the true value of 0.46, which has a strong applicability and a good path optimization effect.