Research on Olympic medal prediction based on GA-BP and logistic regression model Extended data

Background:Predicting the number and distribution of Olympic medals in the future has become a hottopic, but predictingthe number of Olympic medalsis not easyand requires comprehensive consideration of multiple factors such as historical data, athleteperformance,and host country effects.Method:This article uses the GA-BP algorithm model, combined withgenetic algorithm (GA) and backpropagationneural network (BPNN),to optimize the weightsand bias parameters of the BP neural networkusing the global search capability of genetic algorithm, thereby improvingtraining efficiency and prediction performance.By estimating the number of Olympic gold medals and total medals, verifying the accuracy of the model, and predicting the medal table forthe 2028 Los Angeles Olympics. Meanwhile, basedon the synthetic control model, Estonia and China were selected as research subjects to constructa virtual control group and two experimental groupsfor analysis.Including data and code (Matlab)