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Fuzzy mathematics and machine learning algorithms application in educational quality evaluation model

机译:教育质量评价模型的模糊数学与机器学习算法

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摘要

Teaching quality evaluation is a complex non-linear system fitting problem under the influence of many factors. The establishment of teaching quality evaluation is to construct a functional relationship between teaching quality evaluation index and teaching effect. In this paper, the authors analyze the fuzzy mathematics and machine learning algorithms application in educational quality evaluation model. Machine learning method has been well applied in complex problems such as classification, fitting, pattern recognition and so on. It can be used to realize a more comprehensive, reasonable and effective evaluation of the classroom teaching quality of university teachers. The simulation results show that the model can well express the complex relationship between the teaching quality evaluation index and the evaluation results. The theoretical values of the evaluation results are in the corresponding confidence interval, which proves that the machine learning algorithm has good reliability for different teaching quality evaluation problems.
机译:教学质量评价是许多因素影响下复杂的非线性系统拟合问题。教学质量评价的建立是构建教学质量评价指标与教学效果之间的功能关系。本文在教育质量评价模型中分析了模糊数学和机器学习算法。机器学习方法在复杂的问题中得到了很好应用,如分类,拟合,模式识别等。它可用于实现更全面,合理有效地评估大学教师的课堂教学质量。仿真结果表明,该模型能够在教学质量评价指标与评价结果之间表达复杂关系。评估结果的理论值处于相应的置信区间,这证明了机器学习算法对不同的教学质量评估问题具有良好的可靠性。

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