A Study of Tennis Score Evaluation Based on Logistic Regression and LSTM Neural Networks

Abstract

Listen

Translate article

In order to study the performance of athletes in the competition, this paper establishes a comprehensive evaluation mechanism and prediction model through mathematical modeling. Firstly, this paper uses the clustering algorithm to categorize the data and establishes a score evaluation model according to the weights. Then, a momentum evaluation score calculation function was constructed and compared with the results of logistic regression algorithm. Finally, a multi-indicator data system was established to predict the results of the game using the LSTM neural network model. The experimental results show that the model proposed in this paper has a good prediction effect and provides suggestions to the participants.