基于调节优化BP神经网络的高校教学管理评估研究

Research on university teaching management evaluation based on adjusting and optimizing BP neural network

为了提高高校教学管理评估的有效性与智能性,将粒子群优化BP神经网络算法运用于高校教学管理评估数据的分析。采用BP神经网络对教学管理评估指标进行建模,然后采用粒子群对神经网络传递函数的权重和阈值进行深入优化,保证BP神经网络的输出能取得全局最优解。经过实验证明,所提算法对高校教学管理评估对象的预估值与实际值拟合性好,有较强的推广价值。

In order to improve the effectiveness and intelligence of teaching management evaluation in colleges and universities,the particle swarm optimization BP neural network algorithm is applied to data analysis of teaching management evaluation in colleges and universities. The BP neural network is used to perform the mathematical modeling of the evaluation index of teaching management,and then the particle swarm optimization is used to deeply optimize the weights and thresholds of the transfer function of the neural network to ensure that the output of the BP neural network can obtain the global optimal solution. The experimental results show that the proposed algorithm has high fitting performance between the estimated and actual values of the evaluation objects of teaching management in colleges and universities,and has high popularization value.