Research on Logistic Regression Flood Prediction Model Based on Grey Correlation Analysis and K-Means Clustering Analysis

As a natural disaster that will bring serious harm to economic and social development, the probability of flood occurrence is affected by natural climatic factors, and it is also closely related to human practical activities and policies. Firstly, this paper uses the grey correlation algorithm to obtain the correlation degree between different indicators and flood disasters, and then selects the closely related indicators. Then, through K-Means cluster analysis, the probability of flood occurrence was divided into three different risk types: low, medium and high, and the influence of each factor was discussed, so as to establish an early warning evaluation model under different risks. Finally, the logistic regression algorithm is used to accurately predict the flood emission probability. This study can not only help people better predict and respond to flood natural disasters, but also provide a scientific basis for the formulation of ecological policies.