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A Formal Method for Verification and Validation of Neural Network High…

Award Information

Agency:
National Aeronautics and Space Administration
Branch:
N/A
Award ID:
72057
Program Year/Program:
2004 / STTR
Agency Tracking Number:
030126
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
PROLOGIC, INC.
1000 Technology Drive Suite 3140 Fairmont, WV 26554
View profile »
Woman-Owned: No
Minority-Owned: Yes
HUBZone-Owned: No
 
Phase 1
Fiscal Year: 2004
Title: A Formal Method for Verification and Validation of Neural Network High Assurance Systems
Agency: NASA
Contract: NNA04AA20C
Award Amount: $99,963.00
 

Abstract:

Our proposed innovation is to develop neural network (NN) rule extraction technology to a level where it can be incorporated into a software tool, we are calling NNRules, which captures a trained neural network?s decision logic and uses it as a basis for verification and validation (V&V) of the neural network. This formalism has never been attempted. The significance of the NNRules innovation is that: ? The National Aeronautics and Space Administration, the Department of Defense, the Department of Energy, and the Federal Aviation Administration are currently researching the potential of neural networks in mission- and safety-critical systems. ? High assurance neural network applications require rigorous verification and validation techniques. ? The adaptive and ?black box? characteristics of neural networks make verification and validation of neural networks practically intractable. ? Rule-based systems have a more visible, and potentially human readable, decision logic that supports a robust set of verification techniques. ? Neural network rule extraction research has developed algorithms that translate a neural network into an equivalent set of rules. NNRules embeds this technology in a generally usable tool that will dramatically increase the ability to V&V high assurance neural networks.

Principal Investigator:

Marjorie A. Darrah
Principal Investigator
mdarrah@isr.com

Business Contact:

Ken Snyder
Business Official
3043631157
ksnyder@prologic-inc.com
Small Business Information at Submission:

Prologic, Inc.
1000 Technology Drive Fairmont, WV 26554

EIN/Tax ID: 550746190
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
Research Institution Information:
Institute for Scientific Research, Inc.
320 Adams Street, PO Box 2720
Fairmont, WV 26555
Contact: Paul E. Parker, III
Contact Phone: (304) 368-9300
RI Type: Domestic nonprofit research organization