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公开(公告)号：US11822581B2
公开(公告)日：2023-11-21
申请号：US17706706
申请日：2022-03-29
Inventor： Xinjiang Lu , Dejing Dou
CPC classification number: G06F16/285
Abstract: The present disclosure provides a region information processing method and apparatus, and relates to the field of artificial intelligence in computer technologies. The specific implementation is: acquiring a first distance between a first region and a second region, a first object set included in the first region, and a second object set included in the second region; determining spatial dependency information between the first region and the second region according to the first distance; determining object dependency information between the first region and the second region according to the first object set and the second object set; and determining a symbiosis between the first region and the second region according to the spatial dependency information and the object dependency information.
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公开(公告)号：US12148295B2
公开(公告)日：2024-11-19
申请号：US17824966
申请日：2022-05-26
Inventor： Xinjiang Lu , Dejing Dou
IPC: G08G1/01
Abstract: A method of predicting traffic volume, an electronic device, and a storage medium are provided, which relate to a field of artificial intelligence technology, in particular to big data and deep learning technologies The method includes: generating, for a plurality of traffic regions, a function relation graph and a volume relation graph; generating a volume feature of a target traffic region among the plurality of traffic regions, according to a historical volume information of the target traffic region; generating a volume and function relation feature for the target traffic region, based on the function relation graph and the volume relation graph; and predicting a volume of the target traffic region according to the volume feature and the volume and function relation feature.
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公开(公告)号：US11740102B2
公开(公告)日：2023-08-29
申请号：US16864648
申请日：2020-05-01
Inventor： Xinjiang Lu , Yanyan Li , Jianguo Duan , Hui Xiong , Guanglei Du
CPC classification number: G01C21/3682
Abstract: The present disclosure discloses a method, an apparatus, a device, and a storage medium for determining a point of interest area, and relates to the field of automatic driving. The implementation solution is that the method is applied to an electronic device, and includes: receiving a point of interest area determination request input by a first user, the point of interest area determination request including a target area coverage; and acquiring grid data of at least one block within the target area coverage in response to the point of interest area determination request; acquiring, for each block, positioning data of a second user within each preset time period and number of parent points of interest; clustering corresponding grid data according to the positioning data, the grid data and the number of the parent points of interest; determining at least one POI area in each block according to a clustering result.
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公开(公告)号：US11829447B2
公开(公告)日：2023-11-28
申请号：US17173142
申请日：2021-02-10
Inventor： Xinjiang Lu , Nengjun Zhu , Hui Xiong
IPC: G06F17/18 , G06F18/2323 , G06N3/02 , G06F18/25
CPC classification number: G06F18/2323 , G06F17/18 , G06F18/25 , G06N3/02
Abstract: This disclosure discloses a resident area prediction method, apparatus, device and storage medium, involving artificial intelligence technology, big data, deep learning and multi-task learning. The specific implementation plan is: acquiring a resident area data of a target user, and the resident area data including the resident area of the target user and the corresponding resident time; obtaining an association relationship between the resident areas of the target user by inputting the resident area data into an area relationship model, and the area relationship model is used to reflect a position relationship between the areas; determining a time-sequence relationship between the areas visited by the target user, according to the association relationship, the resident time and the visiting POI data; predicting a target resident area of the target user, according to the time-sequence relationship and the basic attribute information of the target user.
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