Development of Mathematical MOOC System Based on BP Neural Algorithm

The emergence of MOOC has constantly affected and changed people's learning methods. With the development and popularization of the Internet and computer technology, it has brought a huge impact on the traditional teaching of mathematics, and has also brought great convenience to our learning. In order to solve the shortcomings of the existing research on the application of BP neural algorithm in the development of mathematical MOOC system, this paper discusses the characteristics of MOOC system and the back propagation and generalization ability of BP neural algorithm, and briefly discusses the Python graphical interface development and system development environment for the application of BP neural algorithm in the development of mathematical MOOC system. Through the analysis of the mathematical formula recognition model by using the full convolution neural network and the bidirectional cyclic neural network, the experimental data analysis shows that HGNN can obtain more useful information from a smaller set of items to identify mathematical formulas. The teaching process design of mathematical MOOC system based on BP neural algorithm is designed, and the mathematical MOOC course is developed using the application of BP neural algorithm in mathematical MOOC system. It provides a reference for the application of mathematical MOOC system under BP neural algorithm.