Momentum Study Based on Logistic Regression Models and BP Neural Networks

Authors

  • Cheng Li
  • Yuquan Ji
  • Jingqi Liu
  • Weisong Zhang

DOI:

https://doi.org/10.54097/

Keywords:

Logistic Regression, AHP-TOPSIS, Kruskal-Wallis H, BP Neural Networks

Abstract

In the context of a game, "momentum" usually refers to a set of events (e.g., consecutive points scored) that create momentum or a trend in a game, which may have a significant impact on the outcome of the game. The purpose of this paper is to investigate how momentum affects the outcome of a game through mathematical modeling. First, an AHP-TOPSIS model is built to calculate the score of each athlete at each moment to quantify and visualize momentum. Second, based on real game data, a Kruskal-Wallis H model test is established to assess the correlation between momentum and score. To predict the fluctuation of players' momentum, logistic regression model was used to predict the momentum fluctuation. Finally, GABP neural network and genetic algorithm are established to visualize the performance data of the players and predict the inflection points during the game. The model proposed in this paper effectively solves the problem of momentum during the game and improves the ability to predict and analyze the game results.

References

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Tiwari, Varun, Prashant Kumar Jain, and Puneet Tandon. "An integrated Shannon entropy and TOPSIS for product design concept evaluation based on bijective soft set." Journal of Intelligent Manufacturing 30 (2019): 1645-1658.

MacFarland, Thomas W., et al. "Kruskal–Wallis H-test for oneway analysis of variance (ANOVA) by ranks." Introduction to nonparametric statistics for the biological sciences using R (2016): 177-211.

Tongle, Xu, Wang Yingbo, and Chen Kang. "Tailings saturation line prediction based on genetic algorithm and BP neural network." Journal of Intelligent & Fuzzy Systems 30.4 (2016): 1947-1955.

Wang, Lihua, et al. "Optimal parameters selection of back propagation algorithm in the feedforward neural network." Engineering Analysis with Boundary Elements 151 (2023): 575-596.

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Published

30-03-2024

Issue

Section

Articles

How to Cite

Li, C., Ji, Y., Liu, J., & Zhang, W. (2024). Momentum Study Based on Logistic Regression Models and BP Neural Networks. Journal of Computing and Electronic Information Management, 12(2), 115-119. https://doi.org/10.54097/

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