John H Tatum

US Patent:

6591255, Jul 8, 2003

Filed:

Apr 5, 2000

Appl. No.:

09/543697

Inventors:

John T. Tatum - Alpharetta GA
Robert J. Jannarone - Atlanta GA

Assignee:

Netuitive, Inc. - Alpharetta GA

International Classification:

G06F 1518

US Classification:

706 25, 706 21

Abstract:

A âRapid Learner Client Serviceâ (RLCS) system that allows a large number of end-users to obtain the benefits of a sophisticated neural-network forecasting system. Rather than purchasing or developing a forecasting system of their own, RLCS clients subscribe to a forecasting service performed by forecasting equipment located at a remote site. This allows a single highly sophisticated forecasting system to meet the forecasting needs of a large number of subscribers. This forecasting service is performed by an RLCS server that periodically and automatically accesses the subscribers computer to obtain a fresh set of input data. Alternatively, the subscribers computer may contact the RLCS server to initiate the process. This input data is then downloaded to the RLCS server, where it is checked and corrected for errors by imputing values for missing or deviant input values. The error-corrected input data is then used to compute a forecast of output values, which are downloaded to the clients computer.

US Patent:

6876988, Apr 5, 2005

Filed:

Mar 16, 2001

Appl. No.:

09/811163

Inventors:

David Helsper - Marietta GA, US
Clayton Wilkinson - Alpharetta GA, US
Robert Zack - Grayson GA, US
John T. Tatum - Alpharetta GA, US
Robert J. Jannarone - Atlanta GA, US
Bernd Harzog - Alpharetta GA, US

Assignee:

Netuitive, Inc. - Alpharetta GA

International Classification:

G06E001/00

US Classification:

706 21, 706 25, 706 26

Abstract:

A method and system for computing a performance forecast for an e-business system or other computer architecture to proactively manage the system to prevent system failure or slow response time. The system is adapted to obtain measured input values from a plurality of internal data sources and external data sources to predict a system's performance especially under unpredictable and dramatically changing traffic levels in an effort to proactively manage the system to avert system malfunction or slowdown. The performance forecasting system can include both intrinsic and extrinsic variables as predictive inputs. Intrinsic variables include measurements of the systems own performance, such as component activity levels and system response time. Extrinsic variables include other factors, such as the time and date, whether an advertising campaign is underway, and other demographic factors that may effect or coincide with increased network traffic.

US Patent:

20120039395, Feb 16, 2012

Filed:

Mar 24, 2010

Appl. No.:

12/999616

Inventors:

Robert J. Jannarone - Atlanta GA, US
John T. Tatum - Atlanta GA, US
Thuy Xuan Cox - Atlanta GA, US
Leronzo Lidell Taturn - Atlanta GA, US
David J. Cohen - Atlanta GA, US

Assignee:

BRAINLIKE, INC. - Atlanta GA

International Classification:

H04N 7/30

US Classification:

37524018, 375E07226

Abstract:

The present invention is be directed to systems and methods that efficiently reduce cluttered data and identify useful information, in real-time. The disclosed auto-adaptive system distinguishes target data in data sets from clutter data that causes low target hit rates and high false alarm rates. Data set features may then be modified to account for changes over time, resulting in auto-adaptive alarm thresholds, higher target hits rates, and lower false alarm rates. In addition, data may be reduced to snip containing target information, while excluding large amounts of clutter data. Thereby, real-time data can be more readily understood and transmitted data can be reduced.