Standardized Management System of Sports Events Based on Deep Learning Algorithm

Abstract

Sports industry has become a new economic growth point, and standardized management of sports events plays an important role in promoting the development of sports industry. Only the scientific and efficient operation of the project can achieve a win-win situation for both economy and society. Sports have typical characteristics of project management, and the development of modern high-level sports events needs more advanced and scientific project management mode and system. Based on the deep learning algorithm, this paper constructs and analyzes the sports project management system, compares and optimizes the deep learning algorithm, and evaluates the satisfaction of track and field competition and the maturity of the management system in a university. The final result shows that the error of the optimized PPO algorithm is the smallest, with a stable mean difference of 1.34, and the simulated score of the optimized management system maturity is 9.17, which is 0.91 points higher than the original one.