AGA-BP algorithm for the evaluation model of teaching quality of dance drama performance

Firstly, the evaluation system was determined, then the AGA and BP neural network algorithms were improved, and finally the entropy weight method was used to construct the dance drama performance teaching quality evaluation model. The optimal hidden layer node of the BP algorithm is 5 and the maximum number of iterations is 120. The corresponding MSE values of the two neural network algorithms, BP and AGA-BP, are 0.0486 and 0.0246 respectively at the maximum number of 120 iterations. The number of convergence of the AGA-BP algorithm is about 6; the convergence value of the sum of squared errors is 0.21, with a 75% improvement in convergence speed and an 80% reduction in the average sum of squared errors. The prediction results of the dance performance quality evaluation show that the prediction accuracy of the AGA-BP prediction model ranges from 0.97 to 1.00.