Intelligent Optimization of College Student Association Management Systems Using Machine Learning Models

With the continuous technological updation of the intelligent management system of college student associations, the organization and management of college student associations has gradually become an important issue in the cultivation of college students. Using a machine learning model to intelligently manage and optimize the service process of the student community education management system can realize the intelligent management of different users through the system. Using a machine learning method can effectively improve the overall performance of the community management system. The community management system tests the response time of a number of online users. This can meet the requirement that the user can simultaneously access the system. In terms of page access success rate, the method in this paper has the highest response success rate in different numbers of people, with a value of 95.4%. When accessing a resource, the system response time increases as the number of visitors increases, and especially when the number of visitors reaches 1,000, the response time of all methods is relatively long.