SBIR Phase I: Nonlinear Modeling in the Presence of Disturbances Using Support Vector Machines

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 0339249
Agency Tracking Number: 0339249
Amount: $99,977.00
Phase: Phase I
Program: SBIR
Awards Year: 2004
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
Pegasus Technologies Inc
5970 Heisley Road, Mentor, OH, 44060
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Stephen Piche
 PI
 (440) 357-7794
 nparikh@pegasustec.com
Business Contact
 Patrick Flaherty
Phone: (440) 358-7740
Email: pflaherty@pegasustec.com
Research Institution
N/A
Abstract
This Small Business Innovation Research Phase I project will investigate novel algorithms for developing nonlinear models based upon time series data that is affected by disturbances. The Box-Jenkins algorithm has been the standard approach over the past few decades for developing models for time-series systems that are affected by disturbances. In recent years, Support Vector Machines (SVMs) have been used to create accurate nonlinear models based upon empirical data. The proposed SBIR research will investigate combining SVM modeling approaches with Box-Jenkins type disturbance rejection techniques. Such an approach would be significantly more computationally efficient, thus, allowing commercialization of the algorithms. Because modeling of nonlinear time-series based systems that are affected by disturbances is commonly encountered across a wide variety of fields including economics, the process industries, engineering, psychology and defense, the proposed research has wide applicability.

* information listed above is at the time of submission.

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