公开(公告)号：US20210385646A1

公开(公告)日：2021-12-09

申请号：US16893832

申请日：2020-06-05

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Yu Liu ,  Baofeng Jiang ,  Yuhong Zheng ,  Hyun Ok Lee

IPC: H04W8/30 ,  H04W8/08 ,  H04W24/08 ,  H04W28/06 ,  H04W28/08 ,  G06N20/00

Abstract: The end-to-end troubleshooting system may use machine learning models to predict the network quality degradation and provide resolution recommendations. The end-to-end troubleshooting system may be a self-evolving closed loop system that helps monitor the network health, provide real-time prediction of network health, and anticipate potential network outages. This intelligent system may provide recommendation resolutions based on the analysis of prediction results.

公开(公告)号：US11665531B2

公开(公告)日：2023-05-30

申请号：US16893832

申请日：2020-06-05

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Yu Liu ,  Baofeng Jiang ,  Yuhong Zheng ,  Hyun Ok Lee

IPC: H04W8/30 ,  G06N20/00 ,  H04W28/06 ,  H04W24/08 ,  H04W8/08 ,  H04W28/08

CPC classification number: H04W8/30 ,  G06N20/00 ,  H04W8/08 ,  H04W24/08 ,  H04W28/06 ,  H04W28/0967

Abstract: The end-to-end troubleshooting system may use machine learning models to predict the network quality degradation and provide resolution recommendations. The end-to-end troubleshooting system may be a self-evolving closed loop system that helps monitor the network health, provide real-time prediction of network health, and anticipate potential network outages. This intelligent system may provide recommendation resolutions based on the analysis of prediction results.

公开(公告)号：US20210103830A1

公开(公告)日：2021-04-08

申请号：US16595662

申请日：2019-10-08

Applicant: AT&T Intellectual Property I, L.P.

Inventor： Yu Liu ,  Baofeng Jiang

IPC: G06N5/04 ,  G06N20/00 ,  G06F16/906 ,  H04W72/04

Abstract: A method includes obtaining device data by a network, wherein the network collects data from a plurality of connected devices, selecting a key performance indicator associated with the plurality of connected devices, clustering the data in accordance with the key performance indicator to form a plurality of clustered data sets, and determining a pattern within at least one of the plurality of clustered data sets to recommend network resource allocations. The pattern may be further used to analyze a second set of device data to determine an updated pattern and wherein the updated pattern is determined based on the pattern and the second set of device data.