Short-term traffic flow prediction method based on gradient boosting decision tree

Abstract

The invention discloses a short-time traffic flow prediction method based on a gradient boosting decision tree, and the method for building a model comprises the steps: 1) carrying out the preprocessing of the traffic flow data of an original highway toll station; 2) performing data analysis, data aggregation (data slicing) and data feature extraction operation on the data; 3) constructing a gradient decision tree model, inputting data into the model and carrying out training work; 4) transplanting the model to a distributed platform, and performing segmentation point sampling statistical optimization and layer-by-layer training optimization adjustment; and 5) constructing a three-layer Stacking model, carrying out multi-model fusion, and then carrying out further training on the data. The related method designed by the invention has the function of rapidly extracting the vehicle flow characteristics, and can predict the vehicle flow in a short time.

Description

technical field [0001] The invention is a short-term traffic flow prediction method based on a gradient lifting decision tree, which is mainly used for short-term traffic flow prediction and the like, and belongs to the technical field of road traffic prediction. Background technique [0002] The short-term traffic flow prediction interval is relatively small, usually 5 to 15 minutes, and it is mainly used for the summary analysis of the three physical quantities of traffic flow, traffic flow speed and traffic flow density. Short-term traffic flow prediction plays an indispensable role in intelligent traffic information system, has great research value, and gradually develops into a hot spot in the field of transportation. The inherent time-varying, nonlinear and highly uncertain characteristics of road traffic bring great difficulties to punctual and real-time traffic flow prediction. In recent years, researchers at home and abroad have carried out in-depth research on urb...

AI Technical Summary

Problems solved by technology

However, when the prediction method based on SVM is used for prediction, the calculation complexity is high and the storage is large. have a great impact

Neural network is an information network formed by connecting a large number of information processing units to each other according to certain rules through the interaction between neurons, so as to realize the rapid processing of network information processing capabilities. value, sensitivity to initial value, slow algorithm convergence speed, weak generalization ability, etc.

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