Author(s)

QianFeng Jin^*, RuiXin Yao

Affiliation(s)

School of Chemistry and Chemical Engineering, North University of China, Taiyuan 030051, Shanxi, China.

Corresponding Author

QianFeng Jin

ABSTRACT

The purpose of this paper is to construct a weighted fusion model to predict the 2028 Olympic medal table with greater accuracy. Firstly, the data is cleansed and a relevant evaluation system is established using the K-Means clustering method. Then, a weighted fusion model integrated with a regression model and a time series model is adopted to predict the medal table of the 2028 Olympic Games. The results are as follows: the United United States is predicted to increase both the number of gold medals and the total number of medals, due to the home field advantage; China's number of gold medals may decrease, due to the abolition of the dominant events; and Japan's number of medals is expected to decrease, due to the loss of home field advantage. The study demonstrates the efficacy of the model in predicting the medal table, thereby providing a reference for countries to formulate their participation strategies and optimise the allocation of resources.

KEYWORDS

Weighted fusion model; K-Means clustering; Olympic Games; Medal prediction

CITE THIS PAPER

QianFeng Jin, RuiXin Yao. Prediction study of 2028 Olympic medal table based on weighted fusion modeling. World Journal of Management Science. 2025, 3(1): 47-52. DOI: https://doi.org/10.61784/wms3058.

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