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    Method and Apparatus for Training Information Adjustment Model of Charging Station, and Storage Medium
    1.
    发明公开
    Method and Apparatus for Training Information Adjustment Model of Charging Station, and Storage Medium 审中-公开

    公开(公告)号：US20230229913A1

    公开(公告)日：2023-07-20

    申请号：US18125327

    申请日：2023-03-23

    Applicant: Beijing Baidu Netcom Science Technology Co., Ltd.

    Inventor： Weijia ZHANG ,  Le ZHANG ,  Hao LIU ,  Jindong HAN ,  Chuan QIN ,  Hengshu ZHU ,  Hui XIONG

    IPC: G06N3/08

    CPC classification number: G06N3/08

    Abstract: A method and apparatus for training an information adjustment model of a charging station, an electronic device, and a storage medium are provided. An implementation comprises: acquiring a battery charging request, and determining environment state information corresponding to each charging station in a charging station set; determining, through an initial policy network, target operational information of each charging station in the charging station set for the battery charging request, according to the environment state information; determining, through an initial value network, a cumulative reward expectation corresponding to the battery charging request according to the environment state information and the target operational information; training the initial policy network and the initial value network by using a deep deterministic policy gradient algorithm; and determining the trained policy network as an information adjustment model corresponding to each charging station.

    POINT-OF-INTEREST RECOMMENDATION
    2.
    发明申请
    POINT-OF-INTEREST RECOMMENDATION 有权

    公开(公告)号：US20220101199A1

    公开(公告)日：2022-03-31

    申请号：US17531132

    申请日：2021-11-19

    Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

    Inventor： Hao LIU ,  Weijia ZHANG ,  Dejing DOU ,  Hui XIONG

    IPC: G06N20/00

    Abstract: A training method for a point-of-interest recommendation model and a method for recommending a point of interest are provided. An implementation solution includes: obtaining training data including a plurality of point-of-interest recommendation requests; determining initialization parameters of the point-of-interest recommendation model; for a first point-of-interest recommendation request among the plurality of point-of-interest recommendation requests, determining a current return for the first point-of-interest recommendation request by utilizing the point-of-interest recommendation model, and determining, based on a second point-of-interest recommendation request initiated after the first point-of-interest recommendation request is completed, a target return for the first point-of-interest recommendation request by utilizing the point-of-interest recommendation model; and adjusting the initialization parameters of the point-of-interest recommendation model based on a difference between the current return and the target return for the first point-of-interest recommendation request, to obtain final parameters of the point-of-interest recommendation model.

    STATION RECOMMENDATION
    3.
    发明申请
    STATION RECOMMENDATION 有权

    公开(公告)号：US20220082397A1

    公开(公告)日：2022-03-17

    申请号：US17531529

    申请日：2021-11-19

    Applicant: BEIJING BAIDU NETCOM SCIENCE TECHNOLOGY CO., LTD.

    Inventor： Weijia ZHANG ,  Hao LIU ,  Dejing DOU ,  Hui XIONG

    IPC: G01C21/34 ,  H04L29/08 ,  G06Q30/06 ,  G06N20/00

    Abstract: A method for recommending a station for a vehicle, a device, and a storage medium are provided. The method comprises: receiving, by a server, an access request from a vehicle; obtaining, based on the access request, a plurality of observation values from a plurality of stations associated with the vehicle, respectively, each observation value is based on a corresponding pre-trained recommendation model, each observation value includes factors associated with access of the vehicle to the station corresponding to the observation value; determining, an action value for the station based on the observation value and the pre-trained recommendation model for the station, the action value for the station indicates a matching degree between the access request and the station; determining a recommended station among the plurality of stations based on the action values of the plurality of stations; and sending to the vehicle an instruction of driving to the recommended station.

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