METHOD AND APPARATUS FOR IDENTIFYING TRAFFIC ACCIDENT, DEVICE AND COMPUTER STORAGE MEDIUM

    公开(公告)号:US20210398427A1

    公开(公告)日:2021-12-23

    申请号:US16951922

    申请日:2020-11-18

    Abstract: A method and apparatus for identifying a traffic accident, a device and a computer storage medium are disclosed, which relates to the technical fields of intelligent traffic and big data. An implementation includes: acquiring road features, environmental features and road traffic stream features; inputting the road features, the environmental features and the road traffic stream features into a pre-trained traffic-accident identifying model to obtain an accident-information identifying result of a road which at least includes an accident identifying result. In the present application, the accident road may be automatically identified according to the road features, the environmental features and the road traffic stream features. Compared with a traditional manual reporting way, timeliness is stronger, and a coverage rate is higher.

    METHOD AND APPARATUS FOR IDENTIFYING UPDATED ROAD, DEVICE AND COMPUTER STORAGE MEDIUM

    公开(公告)号:US20220067370A1

    公开(公告)日:2022-03-03

    申请号:US17410878

    申请日:2021-08-24

    Abstract: The present application discloses a method and apparatus for identifying an updated road, a device and a computer storage medium, and relates to the field of big data technologies. A specific implementation solution is as follows: comparing a road area extracted based on the latest satellite image with a road area extracted based on a historical satellite image, to obtain a candidate updated road; mapping the candidate updated road into road network data according to a coordinate position of the candidate updated road; acquiring a user trajectory set corresponding to the candidate updated road within a recent preset period; and identifying, based on a matching result between the user trajectory set and the road network data, whether the candidate updated road is an actual updated road. Updated roads can be more accurately identified through the method according to the present application.

    POI VALUATION METHOD, APPARATUS, DEVICE AND COMPUTER STORAGE MEDIUM

    公开(公告)号:US20210034993A1

    公开(公告)日:2021-02-04

    申请号:US16936190

    申请日:2020-07-22

    Abstract: A POI valuation method, apparatus, device and computer storage medium are disclosed. The method comprises: obtaining information of first POIs with known values and information of second POIs with unknown values within a regional range; creating a valuation model which is configured to revaluate a first POI using values of surrounding POIs of the first POI, the surrounding POIs including other first POIs and second POIs within a predetermined range of distance from the first POI, and adjusting values of second POIs in the surrounding POIs using an error between a revaluated value of first POI and the known value of the first POI; training the valuation model until the error is minimized; obtaining the values of the second POIs from the valuation model. The solutions may reduce the requirement for manpower and improve the valuation efficiency as compared with manually valuation of POIs one by one.

    METHOD AND APPARATUS FOR ESTABLISHING RISK PREDICTION MODEL AS WELL AS REGIONAL RISK PREDICTION METHOD AND APPARATUS

    公开(公告)号:US20220398465A1

    公开(公告)日:2022-12-15

    申请号:US17620820

    申请日:2021-06-02

    Abstract: A technical solution relates to a big data technology in the field of artificial intelligence technologies. The technical solution includes: acquiring training data including annotation results of a risk grade of each sample region and a risk grade of a district to which each sample region belongs; and training an initial model including an encoder, a discriminator and a classifier using the training data, and obtaining the risk prediction model using the encoder and the classifier after the training process. The encoder performs a coding operation using region features of the sample regions to obtains a feature representation of each sample region; the discriminator identifies the risk grade of the district to which the sample region belongs according to the feature representation of the sample region; the classifier identifies the risk grade of the sample region according to the feature representation of the sample region.

    DATA MINING SYSTEM, METHOD, AND STORAGE MEDIUM

    公开(公告)号:US20210248139A1

    公开(公告)日:2021-08-12

    申请号:US17249939

    申请日:2021-03-19

    Abstract: Embodiments of the present disclosure provide a data mining system, a data mining method, and a storage medium. The data mining system includes a transfer device, a first trusted execution space and a second trusted execution space. The transfer device is configured to receive a data calling request of the second trusted execution space, obtain data to be called from the first trusted execution space according to the data calling request, and provide the data to be called to the second trusted execution space, so as to perform data mining based on the data to be called and the mining-related data to obtain a data mining result and to provide the data mining result to a device of the data user.

    METHOD AND APPARATUS FOR PREDICTION ROAD CONDITION, DEVICE AND COMPUTER STORAGE MEDIUM

    公开(公告)号:US20210241618A1

    公开(公告)日:2021-08-05

    申请号:US17042834

    申请日:2019-03-28

    Abstract: A method and apparatus for predicting a road condition, a device and a computer storage medium are disclosed. The method includes: determining at least two continuous road segments obtained by dividing a navigation path; and performing the following processing on each road segment one by one from the starting point of the navigation path to the end point thereof respectively: determining the moment when the user reaches the road segment processed currently; predicting road condition information of the road segment processed currently at the determined moment; and predicting passing duration of the user at the road segment processed currently based on the road condition information of the road segment processed currently at the determined moment. With such a road-condition prediction mode, the road condition at the moment when the user will reach each road segment in the future may be predicted, and compared with the mode of predicting the road condition based on the user query moment, more accurate road condition information may be provided.

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