Prediction of potential energy on player scoring trend in tennis match based on Hopfield neural network model
Year: 2024
Type: article
Abstract: In tennis, it is very important to catch the direction and trend of the match when the score happens. This paper aims to establish a mathematical model to predict the dynamic change of match progress and the appearance of match points, and explain the role of "momentum" in the match. By mining the real-time match data of 2023 Wimbledon Tennis Open, based on Hopfield neural network and entropy weight method, the technical level, psychological pressure and fatigue level of players in the match are selected as the influencing factors, and the mathematical model between the "momentum" of players and the change of the match flow is established, and the change of the match schedule can be predicted more accurately. The change of momentum may affect the motivation of players, and the choice of a reasonable strategy may be a magic weapon to win the match. It is hoped that this can help the pre-competition training of tennis players and promote the vigorous development of tennis events.
DOI: 10.54097/9emvr219
Authors: Haodong Bian, Shijia Ni, Yuchen Liu
Institution: China University of Mining and Technology
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4404009579