Vehicle model prediction method, device and equipment based on large model, medium and product

Through the model prediction method based on large models, the cargo and vehicle model classification model is used to solve the problem of difficulty in accurately predicting special vehicle models in the prior art, and achieve higher vehicle model prediction accuracy.

CN119719972APending Publication Date: 2025-03-28BEIJING HUITONG TIANXIA LOGISTIC CO LTD
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Patent Information

Application Number
CN202411396223.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-10-08
Publication Date
2025-03-28

AI Technical Summary

Technical Problem

The prior art is difficult to accurately predict the models of special vehicles, such as semi-trailer tractors, because their trailer type cannot be determined by vehicle driving license data.

Method used

The vehicle model prediction method based on large models is adopted, and the vehicle model classification results and vehicle model classification results are determined by obtaining the vehicle name information and product proportion information of the vehicle to be predicted, and multiple cargo classification models are used to determine the vehicle classification results and vehicle model classification results, thereby accurately predicting the vehicle model.

Benefits of technology

Improve the accuracy of vehicle model prediction and can effectively identify and predict models of various vehicles including semi-trailer tractors.

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Abstract

The invention provides a vehicle model prediction method and device based on a large model, equipment, a medium and a product, and relates to the technical field of artificial intelligence, and the method comprises the steps: obtaining the goods name information and goods proportion information of a to-be-predicted vehicle; respectively inputting the goods name information into a plurality of goods classification models, and obtaining an initial goods classification result output by each goods classification model; determining a goods classification result based on each initial goods classification result; and inputting the goods classification result and the goods proportion information into a vehicle type classification model to obtain a vehicle type classification result of the to-be-predicted vehicle output by the vehicle type classification model. Through the mode, the vehicle type of the vehicle can be accurately predicted, and the accuracy of vehicle type prediction is improved.
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