公开(公告)号：US20240281745A1

公开(公告)日：2024-08-22

申请号：US18681946

申请日：2023-08-21

Applicant: STATE GRID SMART GRID RESEARCH INSTITUTE CO., LTD.

Inventor： Congcong SHI ,  Xiuli HUANG ,  Jiaxuan FEI ,  Yujia ZHAI ,  Pengfei YU

IPC: G06Q10/0637 ,  G06Q30/018

CPC classification number: G06Q10/06375 ,  G06Q30/018 ,  G06Q2220/00

Abstract: A federated learning method includes: obtaining a target federated sub-model of a target participating node, the target federated sub-model being obtained upon dividing up a federated model, the federated model comprising at least three federated sub-models, and the target federated sub-model comprising a model parameter and a target feature of the target participating node; obtaining a current network delay and preset instances of optimization of the target feature; determining current instances of optimization on the basis of the difference between the current network delay and a preset network delay corresponding to the preset instances of optimization; performing local optimization on the target feature according to the current instances of optimization; and performing encrypted interaction of an optimization result of the target feature with other participating nodes, so as to optimize a model parameter and determine a target model parameter of the target federated sub-model.