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Evaluation model of art internal auxiliary teaching quality based on artificial intelligence under the influence of COVID-19
2020
Journal of Intelligent & Fuzzy Systems
At present, the evaluation of normal teaching order and teaching quality has been seriously interfered by the impact of COVID-19. In order to ensure the quality of art classroom teaching, this article uses BP neural network technology to build a model for art teaching quality evaluation during the epidemic. Based on the introduction of the BP neural network model and the problems of art teaching quality evaluation, the article focuses on the art teaching quality evaluation indicators and the BP
doi:10.3233/jifs-189267
fatcat:2skogzb46ncnpjrcgo5ki6fzuy