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

Authors: Yueying Xiao

Addresses: Physical Culture Institute, Hunan International Economics University, Changsha, 410205, China

Abstract: 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.

Keywords: adaptive genetic algorithm; AGA; BP; teaching dance performance; quality assessment.

DOI: 10.1504/IJNVO.2023.133869

International Journal of Networking and Virtual Organisations, 2023 Vol.28 No.2/3/4, pp.199 - 213

Received: 25 Aug 2022
Accepted: 18 Jan 2023
Published online: 04 Oct 2023 *

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