Research on Medal Prediction for Events Based on LSTM and BP Neural Networks
DOI:
https://doi.org/10.54097/w4e3z107Keywords:
Summer Olympics, Medal Prediction Model, LSTM Neural Network, BP Neural Network.Abstract
This study focuses on predicting medals in the Summer Olympics. It aims to analyze medal - distribution factors and predict future results through scientific modeling. A multi - input multi - output LSTM model is built to predict each country's medal wins in 2028. Considering athletes' strengths (quantified by past performance), participation arrangements, and historical awards, the model generates a 2028 predicted medal list. The top three gold - medal - winning countries are predicted to be the US, China, and Great Britain, consistent with historical trends. A BP neural network prediction model is also constructed to predict non - winning countries' performance in 2028. Based on the number of participants and athletes' international rankings, etc., the model shows high accuracy (F1 score of 0.93 with prediction errors around 0). It predicts AIN and LAT have a 0.466 and 0.415 probability of winning in 2028. This research offers valuable references for Olympic medal prediction and sports event analysis.
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