公开(公告)号：US20210357809A1

公开(公告)日：2021-11-18

申请号：US17191813

申请日：2021-03-04

Applicant: HITACHI, LTD.

Inventor： Kyosuke HASHIMOTO ,  Soichi TAKASHIGE

IPC: G06N20/00 ,  G06K9/62

Abstract: To efficiently and appropriately improve an inference model when the inference model outputs an inappropriate inference result that affects work. A model improvement system performs inference related to the work using an inference model which is a machine learning model that outputs an inference result by inputting an input matrix, acquires an actual result which is information acquired by actually performing work to be inferred by the inference model, determines whether or not the inference result is an inappropriate content that affects the work by comparing the inference result with the actual result, divides a part of the input matrix that outputs the inference result that affects the work from the input matrix, and generates an inference model that outputs an inference result that does not affect the work when the part divided from the input matrix is input as an input matrix.

公开(公告)号：US20180270132A1

公开(公告)日：2018-09-20

申请号：US15758739

申请日：2016-03-24

Applicant: Hitachi, Ltd.

Inventor： Kyosuke HASHIMOTO ,  Hitoshi YABUSAKI ,  Junji KINOSHITA

IPC: H04L12/26

CPC classification number: H04L43/0823 ,  H04L41/0213 ,  H04L41/064 ,  H04L41/0893 ,  H04L43/16

Abstract: An anomaly detection apparatus for detecting data flow anomalies classes a plurality of data flows on the basis of similarity in time series changes in the data amounts of the data flows; calculates a correlation coefficient at a normal time and a correlation coefficient at a certain timing between at least two data flows belonging to the same class; and determines that at least one of the at least two data flows is anomalous when a difference between the correlation coefficient at the normal time and the correlation coefficient at the certain timing is greater than a predetermined threshold.