Formation mechanism and early warning of financial crisis combined with data mining technology

This paper aims to deeply discuss the formation mechanism of financial crisis (FC). The sparrow search algorithm (SSA) is used to improve the BP neural network (BPNN) to solve the problem that the BPNN is easy to fall into local extreme values. The tent chaotic mapping is used to improve the sparrow search algorithm. Combined with experimental analysis, it can be seen that the R-value of the sparrow search algorithm - back propagation neural network (SSA-BPNN) model training set is 1, the R-value of the validation set is 0.99981, the R-value of the test set is 0.99994, and the R-value of the entire set is 0.99996. Through model comparison and analysis, the data mining model combined with SSA-BPNN has higher accuracy and system performance in the analysis of the FC formation mechanism and its early warning compared with the traditional model.