公开(公告)号：US10805931B2

公开(公告)日：2020-10-13

申请号：US16286844

申请日：2019-02-27

Applicant: Korea Advanced Institute of Science and Technology

Inventor： Dong Ho Cho ,  Dong Jin Ji ,  Hyuk Joon Lee

IPC: H04W72/04 ,  H04W28/16 ,  G06N3/02

Abstract: Disclosed is a reinforcement learning-based resource allocation method for a wireless backhaul network, which is performed by a resource allocation apparatus. The method includes estimating locations of a plurality of base stations on the basis of channel state information (CSI) measured by the plurality of base stations; and allocating resources of the wireless backhaul network to the plurality of base stations using a reinforcement learning neural network having the locations as an input.

公开(公告)号：US20190385696A1

公开(公告)日：2019-12-19

申请号：US16428715

申请日：2019-05-31

Applicant: Korea Advanced Institute of Science and Technology

Inventor： DongHo CHO ,  Hyein SEO ,  YongJoon SONG ,  GyuBum HAN ,  Dong Jin Ji

IPC: G16B5/20 ,  G16B5/30 ,  G16B35/10 ,  G16B40/00

Abstract: Provided is a method for diagnosing a disease risk based on complex genetic information network analysis. In the method for diagnosing a disease risk based on complex genetic information network analysis according to the present invention, it is possible to deduce a stable correlation with a disease from a small number of genetic information combination by introducing an optimization method or learning method, and it is possible to provide a genetic information correlation based on a network model. A diagnosis technology satisfying accuracy and economical efficiency enough to be commercially used in an actual medical field by using the correlation between the genetic information and the disease deduced in the present invention will be secured. Further, the biomarker deduced in the present invention will be commercially used in manufacturing a medical device including a diagnosis chip and terminal and in disease diagnosis service.