Analysis of Teaching Influencing Factors and Teaching Reform of Numerical Analysis Course Based on BP Neural Network

Numerical analysis course has important guiding significance for data analysis ability of science and engineering graduate students. Based on BP neural network, we study the teaching influencing factors and teaching reform analysis of numerical analysis course. The teaching quality evaluation of numerical analysis is constructed based on BP neural network. The course of numerical analysis is evaluated from the aspects of classroom teaching, extracurricular development, students' knowledge reserve, and teaching results. 0.820675 is the related coefficient between the predicted value of the neural network and the actual value of questionnaire results, which shows that the constructed teaching quality evaluation model is reliable. Through the related coefficient analysis of the data, the main factors affecting the quality of teaching are obtained to provide new direction and orientation for teaching reform.