In the process of establishing evaluation index system of physical education, the traditional methods setting weights for each indicator mainly include analytic hierarchy process, fuzzy comprehensive evaluation method, and Delphi method, etc. These methods mostly rely on experience, which is strongly influenced by artificial factors and cannot be avoided. Because artificial neural network model has the ability of highly nonlinear function mapping, it is applied to the teaching quality evaluation system of physical education. Besides, the weight value of neural network is optimized by genetic algorithm. The experiment results show that the proposed scheme is feasible.
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Bin Hu (2017) studied this question.
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