Intelligent Sports Prediction Analysis System Based on Edge Computing of Particle Swarm Optimization Algorithm

In recent years, the level of competition in my country's sports field has developed rapidly, and the public's attention to sports competitions has also increased. The forecast and analysis of sports events have therefore gathered the attention of a broad audience. The sports forecast news reports issued by various sports news media have become popular entertainment news topics by many readers. The research purpose of this article is to explore the research and design of intelligent sports prediction analysis systems based on particle swarm optimization algorithm. Under the background that artificial intelligence has been widely used in various industries, this article combines the predictive performance of the edge computing of the particle swarm optimization algorithm in artificial intelligence and the traditional sports event predictive analysis method to design an intelligent sports predictive analysis system. After understanding the methods and research status of sports events prediction analysis through literature research, this article conducts demand analysis and feasibility analysis on the intelligent sports prediction analysis system based on the main factors that need to be considered in sports prediction analysis and the current application of particle swarm optimization algorithms. According to the demand analysis, the functional modules of the intelligent sports predictive analysis system are designed, and a systematic test experiment is carried out on the predictive performance of the intelligent sports predictive analysis system for sports events. Experiments show that the prediction accuracy of the intelligent sports prediction analysis system for sports events is higher than that of traditional sports events prediction methods, which can reach about 89.6%, and it can better cater to the interests of readers who are concerned about sports events.