Traffic state prediction method and device and electronic equipment

Abstract

The invention provides a traffic state prediction method and device and electronic equipment, and relates to the technical field of intelligent traffic. The method comprises the steps: generating a plurality of chromosome units, each chromosome unit being used for representing a class of space-time convolution network models; calculating a loss value of the space-time convolutional network model corresponding to each chromosome unit in the plurality of chromosome units based on a sample set; updating the plurality of chromosome units according to the loss values of the space-time convolutional network models corresponding to the plurality of chromosome units, and returning to the step of calculating the loss value of the space-time convolutional network model corresponding to each chromosome unit in the plurality of chromosome units based on the sample set until a target chromosome unit meeting preset conditions is determined; determining a pre-trained space-time convolutional network model based on the space-time convolutional network model corresponding to the target chromosome unit; and predicting the traffic state based on the pre-trained space-time convolutional network model. According to the invention, the accuracy of traffic state prediction can be improved.

Description

technical field [0001] The invention relates to the technical field of intelligent transportation, in particular to a traffic state prediction method, device and electronic equipment. Background technique [0002] With the continuous advancement of the urbanization process, the importance of intelligent transportation is getting higher and higher. Traffic status prediction is an important part of intelligent transportation. The predicted traffic status information can help people make travel route decisions, thereby alleviating traffic congestion and improving the happiness of urban living. In the prior art, the traffic state is usually predicted by statistical methods, and the traffic state at the next moment is predicted by counting the number of vehicles and the speed of vehicles within a period of time. However, the statistical method relies on experience to predict the traffic state, and the accuracy of predicting the traffic state is relatively low. Difference. Cont...

AI Technical Summary

Problems solved by technology

[0003] The embodiment of the present invention provides a traffic state prediction method, device and electronic equipment to solve the problem in the prior art that predicting the traffic state through statistical methods has poor accuracy in predicting the traffic state

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