公开(公告)号：US20230368066A1

公开(公告)日：2023-11-16

申请号：US17663464

申请日：2022-05-16

Applicant: Juniper Networks, Inc.

Inventor： Shruti JADON ,  Ajit Krishna PATANKAR

IPC: G06N20/00

CPC classification number: G06N20/00

Abstract: A device may receive site data identifying raw data or key performance indicators associated with a plurality of sites, and may calculate a similarity score matrix based on the site data. The device may group the site data into data clusters based on the similarity score matrix, and may identify training data and validation data based on the data clusters. The device may generate a meta model, and may train the meta model based on the training data. The device may validate the meta model based on the validation data, and may create site-specific models, for each of the plurality of sites, based on the meta model and the site data. The device may utilize the site-specific models with corresponding new site data of the plurality of sites to generate predictions for the plurality of sites.

公开(公告)号：US20240095603A1

公开(公告)日：2024-03-21

申请号：US17806550

申请日：2022-06-13

Applicant: Juniper Networks, Inc.

Inventor： Shruti JADON ,  Ajit Krishna PATANKAR

IPC: G06N20/20

CPC classification number: G06N20/20 ,  G16Y40/20

Abstract: A device may receive time series data, and may define a first quantity of steps into past data utilized to make future predictions, a second quantity of steps into the future predictions, and a third quantity of steps to skip in the future predictions. The device may determine whether the second quantity is equal to the third quantity. When the second quantity is equal to the third quantity, the device may process the time series data, with a plurality of machine learning models, to generate a plurality of future predictions that do not overlap, may merge the plurality of future predictions into a list of future predictions, and may provide the list for display. When the second quantity is not equal to the third quantity, the device may process the time series data, with the plurality of machine learning models, to generate another plurality of future predictions that do overlap.