Expressway toll station traffic flow big data prediction method based on multi-target regression

Abstract

The invention discloses an expressway toll station traffic flow big data prediction method based on multi-target regression. The method comprises the following steps: 101, carrying out preprocessing operation on data; 102, marking the data; 103, performing feature engineering construction operation on the data; 104, constructing a multi-target regression model combining the specific characteristics of the target and the target correlation; and 105, predicting the traffic flow of the toll station every 20 minutes from 8 o'clock to 10 o'clock according to the historical traffic flow data of thetoll station, the weather data and other information through the established model. The method mainly preprocesses and analyzes historical traffic flow data, weather data and other information of a toll station to extract characteristics; a multi-target regression model combining target specific characteristics and target correlation is established, and the traffic flow from 8 o'clock to 10 o'clock per 20 minutes is predicted, so that a traffic management department can take measures in time by using big data to reduce the congestion of the toll station.

Description

technical field [0001] The invention belongs to the technical field of machine learning and big data processing, in particular to a large data prediction method for traffic flow at expressway toll stations based on multi-objective regression. Background technique [0002] Highway tollbooths are a well-known bottleneck in transportation networks. During peak hours, long queues at toll booths can overwhelm traffic authorities. Effective pre-emptive countermeasures are necessary to address this problem. These countermeasures include speeding up the toll collection process, temporarily opening more lanes, adaptively adjusting traffic signals, and more. But to take these steps, traffic authorities must receive reliable forecasts of future traffic volumes. These flows are not just one time period, but multiple time periods. This is a typical multi-objective regression problem. Therefore, a large data prediction method for expressway toll station traffic flow based on multi-obj...

AI Technical Summary

Problems solved by technology

The features corresponding to each target are the same, there is no way to build target-specific features for each target, and the correlation between targets is not considered

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