公开(公告)号：US11295331B2

公开(公告)日：2022-04-05

申请号：US16918668

申请日：2020-07-01

Applicant: X Development LLC

Inventor： Nanzhu Wang ,  Chunfeng Wen ,  Yueqi Li

IPC: G06Q10/00 ,  G06Q30/02 ,  G06Q10/04 ,  G06N20/00 ,  G06F16/29 ,  A01B79/00 ,  G06Q10/06

Abstract: Implementations are described herein for using machine learning to determine whether candidate crop fields are suitable for management by particular agricultural entities. In various implementations, a machine learning model may be applied to input data to generate output data. The input data may include a first plurality of data points corresponding to field-level agricultural management practices of an agricultural entity. The output data may be indicative of one or more predicted outcomes of the agricultural entity implementing the field-level agricultural management practices on one or more candidate crop fields not currently managed by the agricultural entity. Based on one or more of the predicted outcomes, one or more computing devices may be caused to provide a user associated with the agricultural entity with information about one or more of the candidate crop fields, and/or one or more parameter inputs of a graphical user interface may be prepopulated.

公开(公告)号：US20220188854A1

公开(公告)日：2022-06-16

申请号：US17689218

申请日：2022-03-08

Applicant: X Development LLC

Inventor： Nanzhu Wang ,  Chunfeng Wen ,  Yueqi Li

IPC: G06Q30/02 ,  G06Q10/04 ,  G06N20/00 ,  G06F16/29 ,  A01B79/00 ,  G06Q10/06

Abstract: Implementations are described herein for using machine learning to determine whether candidate crop fields are suitable for management by particular agricultural entities. In various implementations, a machine learning model may be applied to input data to generate output data. The input data may include a first plurality of data points corresponding to field-level agricultural management practices of an agricultural entity. The output data may be indicative of one or more predicted outcomes of the agricultural entity implementing the field-level agricultural management practices on one or more candidate crop fields not currently managed by the agricultural entity. Based on one or more of the predicted outcomes, one or more computing devices may be caused to provide a user associated with the agricultural entity with information about one or more of the candidate crop fields, and/or one or more parameter inputs of a graphical user interface may be prepopulated.

公开(公告)号：US20220005055A1

公开(公告)日：2022-01-06

申请号：US16918668

申请日：2020-07-01

Applicant: X Development LLC

Inventor： Nanzhu Wang ,  Chunfeng Wen ,  Yueqi Li

IPC: G06Q30/02 ,  G06Q10/04 ,  G06Q10/06 ,  G06F16/29 ,  A01B79/00 ,  G06N20/00

Abstract: Implementations are described herein for using machine learning to determine whether candidate crop fields are suitable for management by particular agricultural entities. In various implementations, a machine learning model may be applied to input data to generate output data. The input data may include a first plurality of data points corresponding to field-level agricultural management practices of an agricultural entity. The output data may be indicative of one or more predicted outcomes of the agricultural entity implementing the field-level agricultural management practices on one or more candidate crop fields not currently managed by the agricultural entity. Based on one or more of the predicted outcomes, one or more computing devices may be caused to provide a user associated with the agricultural entity with information about one or more of the candidate crop fields, and/or one or more parameter inputs of a graphical user interface may be prepopulated.