Power Outage Prediction of Flood Disaster Based on Random Forest Classification

The flood disaster has caused extensive damage and economic losses worldwide, and the Power outage caused by it is particularly common and has an important impact. Therefore, it is of great significance to use effective methods to predict Power outage in advance of flood disaster. A method of using random forest classification to predict the probability of Power outage in flood disaster is proposed. Firstly, supervised learning, decision tree and ensemble learning methods are introduced as the basis of random forest. Secondly, the basic principle of random forest is elaborated in detail. Thirdly, based on the random forest classification method, according to the steps of feature selection, model training and model evaluation, a flood disaster Power outage prediction model is constructed. Finally, a set of data is used to verify and analyze the model, and the performance and accuracy of the model are evaluated. The results show that this method has high accuracy in predicting the probability of Power outage in flood disaster, and provides an effective strategy for the prediction of Power outage in flood disaster in advance, which has important practical application value.