A vehicle feature data processing method and a vehicle risk prediction model training method

Abstract

The invention provides a vehicle characteristic data processing method and a vehicle risk prediction model training method. The vehicle feature data processing method comprises the steps of obtainingat least one kind of original data, determining a plurality of required first feature factors from the original data, then selecting feature points from the track points, performing hierarchical storage on the feature points, determining connection lines between the feature points corresponding to different levels, and performing associated storage on the plurality of first feature factors and thefeature points or the connection lines between the feature points; The vehicle risk prediction model training method comprises the steps of training a vehicle risk prediction model by using a plurality of pieces of sample data, wherein each piece of sample data comprises a sample mark used for representing whether the vehicle has an accident or not; and at least one first feature factor and / or atleast one second feature factor stored on the associated feature points or the connecting lines between the feature points corresponding to a certain track level, so that the problem of low accuracyof an existing vehicle risk prediction model is solved.

Description

technical field [0001] The invention relates to the field of automobile insurance, in particular to a vehicle characteristic data processing method and a vehicle risk prediction model training method. Background technique [0002] With the advent of the Internet era and the development of technology globalization, the mobile Internet is constantly penetrating into various fields of society and economy. Similarly, the Internet of Vehicles under the Internet is also penetrating into the automobile insurance industry. Therefore, the automobile insurance industry based on the Internet of Vehicles has Huge development prospects. Among them, Internet of Vehicles technology and big data technology are the core driving forces for the future development of the insurance industry. In such an era background, the research on the Internet of Vehicles insurance was carried out, and the UBI system research in the era of big data was proposed. [0003] In the prior art, vehicle body data i...

AI Technical Summary

Problems solved by technology

However, due to the incomplete data characteristics and the fact that only one algorithm is used for calculation when training the model, the accuracy of the existing UBI prediction model is low, and the accuracy of predicting the probability of accident of the vehicle is not high.

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