Construction of university education management decision support system based on neural network algorithm

The purpose of this paper is to construct a Decision Support System (DSS) for university education management based on neural network algorithm, so as to improve the decision-making level of university administrators for school operation. By fully integrating multi-source and multi-dimensional university management data, the system adopts BP neural network (BPNN) for intelligent analysis and learning. The experimental results show that the proposed system has achieved remarkable performance advantages in many evaluation indexes. Through the cleverly designed BPNN structure, the system realizes the intelligent modeling of university management data, which can better adapt to the complexity and nonlinear relationship of data. In addition, by adjusting and optimizing the parameters of the neural network algorithm, the system shows stable performance in training and testing. The experimental results show that the accuracy, recall and Precision of the proposed system are all over 80%, which verifies its effectiveness in the field of university education management. Compared with traditional methods, the system shows better generalization ability and performance advantages. This study provides an intelligent and comprehensive decision-making tool for university administrators, which is expected to promote the scientific management and sustainable development of universities.