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
Amount:
$374,996.00
Award Year:
2003
Program:
SBIR
Phase:
Phase II
Contract:
DAAH0103CR162
Agency Tracking Number:
02SB1-0174
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
PSYNAPSE TECHNOLOGIES, LLC
1000 Thomas Jefferson St. N.W., Washington, DC, 20007
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
095609165
Principal Investigator:
Gary Jackson
President and CEO
(202) 298-2660
gjackson@psynapsetech.com
Business Contact:
Stephanie Jackson
Vice President of Adminis
(202) 298-2661
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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