Sports Performance Prediction Model Based on Stochastic Simulation Algorithm

Abstract

AbstractWith the continuous in-depth study of random theory, the description of various events in life is becoming more and more scientific. The methods provided by stochastic process theory are very important to mathematics. The purpose of this article is to study sports performance prediction models based on random simulation algorithms. Introduce the stochastic simulation based on Markov process, firstly give a general overview of the problems involved in the Markov process, and then construct the prediction model of the stochastic simulation algorithm in detail. Track and field performance is the essential test of athletic ability. With the help of the complementarity between the advantages of Markov and the stochastic simulation algorithm, the improved Markov stochastic simulation algorithm prediction model analyzes and predicts the annual best results of the women’s 1000 m in M college. The experimental results show that it is similar to the gray GM prediction model. In comparison, the accuracy is improved to 98.20% .KeywordsStochastic simulationSimulation algorithmSports performancePredictive model