Design and development of training quality management system of enterprise university and application of data mining technology

Abstract:
In view of the shortcomings of high cost, low efficiency and single and backward training management system of current physician training management, this paper deeply discusses the development status and research background of cloud computing and existing physician training quality management system in enterprise universities. By improving the BP neural network, the MSC-BP2 algorithm is obtained, and on the basis of the improved algorithm, a physician training management system based on the OpenStack cloud platform is proposed. Finally, the cloud computing technology framework is analyzed and the MSC-BP2 neural network is tested to realize the sharing of traditional doctor training network, which shows the applicability and superiority of cloud computing in traditional doctor training. The experimental results show that setting the acceleration ratio of equilibrium point to 8 can obtain an effective optimization space, and when the conditions are superior, the physician training model can be optimized and the speed of model training can be improved. Compared with the unimproved BP neural network algorithm and the MSC-BP1 algorithm, the error between the evaluation value of MSC-BP2 algorithm proposed in this paper and the evaluation value of expert is the smallest, and the evaluation score is the highest. Therefore, MSC-BP2 network can improve the management efficiency of physician training.