Jeffery Michael Robinson

US Patent:

20190377653, Dec 12, 2019

Filed:

Aug 23, 2019

Appl. No.:

16/549770

Inventors:

- McLean VA, US
Mark Schutt - Chesterfield VA, US
Jeffery Robinson - Richmond VA, US

Assignee:

Capital One Services, LLC - McLean VA

International Classification:

G06F 11/34
G06Q 10/06

Abstract:

This disclosure relates generally to system modeling, and more particularly to systems and methods for modeling computer resource metrics. In one embodiment, a processor-implemented computer resource metric modeling method is disclosed. The method may include detecting one or more statistical trends in aggregated interaction data for one or more interaction types, and mapping each interaction type to one or more devices facilitating the transactions. The method may further include generating one or more linear regression models of a relationship between device utilization and interaction volume, and calculating one or more diagnostic statistics for the one or more linear regression models. A subset of the linear regression models may be filtered out based on the one or more diagnostic statistics. One or more forecasts may be generated using the remaining linear regression models, using which a report may be generated and provided.

US Patent:

20160379143, Dec 29, 2016

Filed:

Jun 16, 2016

Appl. No.:

15/184501

Inventors:

- McLean VA, US
Mark Schutt - Chesterfield VA, US
Jeffery Robinson - Richmond VA, US

International Classification:

G06Q 10/06
G06F 17/50

Abstract:

This disclosure relates generally to system modeling, and more particularly to systems and methods for modeling computer resource metrics. In one embodiment, a processor-implemented computer resource metric modeling method is disclosed. The method may include detecting one or more statistical trends in aggregated interaction data for one or more interaction types, and mapping each interaction type to one or more devices facilitating the transactions. The method may further include generating one or more linear regression models of a relationship between device utilization and interaction volume, and calculating one or more diagnostic statistics for the one or more linear regression models. A subset of the linear regression models may be filtered out based on the one or more diagnostic statistics. One or more forecasts may be generated using the remaining linear regression models, using which a report may be generated and provided.