Erkennung von Anomalien in Zeitreihen von Maschinellem Lernen

Details

Veröffentlichungs-Nr.

EP4765755

Anmeldetag

24. Mai 2022

Veröffentlichung

24. Juni 2026

Rechtsraum

EP

IPC

H04L41/16

Abstract

A method (400) includes receiving a time series anomaly detection query (20) from a user (12) and training one or more models (212) using a set of time series data values (152). For each respective time series data value in the set, the method includes determining, using the trained models, an expected data value for the respective time series data value and determining a difference between the expected data value and the respective time series data value. The method also includes determining that the difference between the expected data value and the respective time series data value satisfies a threshold (314). In response to determining that the difference between the expected data value and the respective time series data value satisfies the threshold, the method includes determining that the respective time series data value is anomalous and reporting the anomalous respective time series data value (152A) to the user.

Anmelder

Firma

Google LLC

Land

🇺🇸 USA