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针对神经网络的结构特性、自适应和自学习功能,提出了基于BP神经算法建立高职教师教学质量评价系统,确定了系统的数学模型,采用各评价指标作为其输入,教学效果作为输出。该模型在收敛速度、网络的适应能力方面是可行的、适用的。实验结果表明:该数学模型克服了传统分析、评价教学过程中的复杂性和人为因素干扰,具有方便、准确、可靠、快速的特点,辨识精度高。
According to the structural characteristics, self-adapting and self-learning function of neural network, a teaching evaluation system based on BP neural network is proposed to establish the teaching quality of higher vocational teachers. The mathematical model of the system is established. Each evaluation index is used as input and the teaching effect is output. The model is feasible and applicable in terms of convergence rate and network adaptability. The experimental results show that the mathematical model overcomes the traditional analysis, evaluates the complexity of teaching process and the interference of human factors, and has the characteristics of convenience, accuracy, reliability and speed, and high recognition accuracy.