Weight stacking decision tree-based short-time public transport passenger flow prediction method and system

The invention discloses a short-time public transport passenger flow prediction method and system based on a weight stacking decision tree. The method comprises the following steps: 1) preprocessing bus IC card data, and aggregating the data into hour passenger flow data; 2) acquiring feature data of a to-be-detected route according to the location of the bus route and the time interval of the historical passenger flow, establishing a feature matrix and performing normalization operation; 3) carrying out independence test on the obtained features, carrying out correlation test on different features and prediction labels, and carrying out normal distribution test on the features; 4) constructing a weight stacking gradient lifting tree model; 5) training the training set through the weight stacking gradient boosting tree model, and then predicting the passenger flow in the prediction period to obtain a prediction result. The method has higher prediction precision and prediction stability, can give full play to the value of big data in the public transport field, effectively extracts the relevance between the multi-source impact factor and the passenger flow, and achieves the more accurate prediction of the short-term passenger flow of the public transport.