Intelligent Classification Method of Digital Twin Airport Hazard Based on ID3 Algorithm

In order to enhance airport hazard management and enable intelligent decision-making in digital twin environments, this paper proposes an intelligent hazard classification method based on the ID3 algorithm. The method utilizes a 6-dimensional hazard feature model generated by combining “human-machine-environment-management” factors with hazard sources and types. It trains an ID3 decision tree using a subset of samples as the training set and evaluates the decision accuracy using the remaining samples as the testing set. The effectiveness of the proposed hazard classification model is demonstrated through a case study using an airport hazard database, showcasing high classification accuracy and the ability to refine and optimize the model using historical data. This method provides decision support for hazard classification management in digital twin airports.