Research on efficiency evaluation of financial management in universities based on GWO-BPNN algorithm

In order to improve the accuracy of back propagation neural network BPNN model in the evaluation of financial management efficiency in universities, the grey wolf optimization (GWO) algorithm is innovatively combined, and the GWO-BPNN intelligent algorithm is proposed. By optimizing the initial weights and thresholds, the algorithm improves the stability and prediction accuracy of the model, and provides a more reliable method for the evaluation of financial management efficiency in universities. In order to verify the actual effect of the algorithm, different levels of financial data sets of a university in China are selected for empirical research. The experimental results show that the coefficient of the financial risk regression model is as high as 0.99351, which fully proves the remarkable effect of using GWOBPNN algorithm in the financial internal control management of universities.