US 12,327,199 B2
Multi-scale exponential-smoothing forecaster for time series data
Arun Kumar Jagota, Sunnyvale, CA (US)
Assigned to Salesforce, Inc., San Francisco, CA (US)
Filed by salesforce.com, inc., San Francisco, CA (US)
Filed on Jan. 8, 2021, as Appl. No. 17/144,896.
Prior Publication US 2022/0222547 A1, Jul. 14, 2022
Int. Cl. G06N 5/04 (2023.01); G06F 9/50 (2006.01); G06F 16/28 (2019.01); G06N 20/00 (2019.01)
CPC G06N 5/04 (2013.01) [G06F 9/5083 (2013.01); G06F 16/283 (2019.01); G06N 20/00 (2019.01); G06F 2209/5019 (2013.01); G06F 2209/503 (2013.01); G06F 2209/508 (2013.01)] 20 Claims
OG exemplary drawing
 
1. A system for a multi-scale exponential-smoothing forecaster for time series data, the system comprising:
one or more processors; and
a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to:
receive time series data indicative of a resource utilization by an application over time, wherein the time series data includes a current value indicative of a current utilization of a resource by the application at a current time;
determine a forecasted future value in the time series data, wherein the determining includes:
determining, for the current value, a first estimate of the current value based on a first prior value and a first velocity indicating a first rate of change associated with the first prior value, wherein the first prior value precedes the current value in the time series data by a first time interval;
determining, for the current value, a second estimate of the current value based on a second prior value and a second velocity indicating a second rate of change associated with the second prior value, wherein the second prior value precedes the current value in the time series data by a second, different time interval;
determining a first weight indicative of an accuracy of the first estimate by comparing the first estimate to the current value;
determining a second weight indicative of an accuracy of the second estimate by comparing the second estimate to the current value; and
forecasting the future value by:
determining first and second estimates of the future value based on the current value and the first prior value; and
combining the first and second estimates of the future value adjusted based on the first and second weights in a manner that implements multi-scale exponential-smoothing; and
provide, via a user interface, an alert associated with the resource utilization based on the determined forecasted future value satisfying a threshold.