A Hybrid Neural Network and Rule-Based System for Behavioral CBRN (BCBRN) Real-Time Assessment

Award Information
Agency: Department of Defense
Branch: Defense Advanced Research Projects Agency
Contract: DAAH0103CR162
Agency Tracking Number: 02SB1-0174
Amount: $374,996.00
Phase: Phase II
Program: SBIR
Awards Year: 2003
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
1000 Thomas Jefferson St. N.W., Washington, DC, 20007
DUNS: 095609165
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Gary Jackson
 President and CEO
 (202) 298-2660
 gjackson@psynapsetech.com
Business Contact
 Stephanie Jackson
Title: Vice President of Adminis
Phone: (202) 298-2661
Email: sjackson@psynapsetech.com
Research Institution
N/A
Abstract
The ABC Behavioral model, pattern classification methodology, and an expert, rule based system are proposed as key approaches to: (1) capture relevant historical data from actual CBRN cases to extract patterns among environmental events and organizationcharacteristics, and (2) augment historical data with CBRN agent-specific characteristics to provide an enhanced predictive system. The purpose of the application is to construct a CBRN assessment instrument accessible on the web that may be used todetermine the likelihood of threat of CBRN attack as directed toward the organization completing the assessment and, as a result of the assessment, to receive recommendations if threat is determined. Using well-tested, reliable, and validated modelingmethodologies developed for DARPA, the CBRN assessment instrument proposal expands this past work to the specific area of asymmetric CBRN threat and applied threat assessment.

* Information listed above is at the time of submission. *

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