Evaluation and Prediction of Sport Status Based on Variable Step Size Hidden Markov Model

Abstract

Abstract. In order to early accurately assess and predict the exercise state of sports, based on Hidden Markov Model, the autocorrelation coefficient of selection and prediction of future events was significantly related to state step according to the history of the state of the event, the weight of a future state prediction based on information entropy was established as the time-varying forgetting factor; the time-varying forgetting factor was introduced, and the time varying tracking factor was established by the active window mechanism, transition probability matrix was adjusted by the relationship between the state information of event history and difference step state of transition probability matrix. Thus, the state predicting method based on variable step recursive Hidden Markov Model was established. Finally, through specific examples, this method can accurately assess and predict the exercise state of sports and improve analysis accuracy and ability.