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Teaching Quality Evaluation Research Based on Neural Network for University Physical Education

机译:基于神经网络的大学体育教学质量评价研究

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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.
机译:在建立体育教学评价指标体系的过程中,传统的为指标设置权重的方法主要有层次分析法,模糊综合评价法,德尔菲法等。这些方法主要依靠经验,受到人为因素的强烈影响。因素,是无法避免的。由于人工神经网络模型具有高度非线性的函数映射能力,因此被应用于体育教学质量评价体系中。此外,通过遗传算法对神经网络的权重进行了优化。实验结果表明,该方案是可行的。

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