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

B. Hu
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引用次数: 7

Abstract

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.
基于神经网络的大学体育教学质量评价研究
在建立体育教育评价指标体系的过程中,传统的指标权重确定方法主要有层次分析法、模糊综合评价法、德尔菲法等。这些方法大多依靠经验,受人为因素影响较大,无法避免。由于人工神经网络模型具有高度非线性函数映射的能力,将其应用于体育教学质量评价体系中。此外,采用遗传算法对神经网络的权值进行优化。实验结果表明,该方案是可行的。
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