Hybrid Neural Network/Parametric Models for State and Trait Estimation in Performance Modeling

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$99,998.00
Award Year:
2005
Program:
STTR
Phase:
Phase I
Contract:
W81XWH-05-C-0155
Agency Tracking Number:
A054-029-0337
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Pulsar Informatics, Inc.
1 Old Dominion University, Norfolk, VA, 23529
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
158273743
Principal Investigator:
Daniel Mollicone
President
(215) 520-2630
dan@pulsarinformatics.com
Business Contact:
Daniel Mollicone
President
(215) 520-2630
dan@pulsarinformatics.com
Research Institution:
VMASC
Kevin McKlesky
1 Old Dominion University
Norfolk, VA, 23529
(757) 686-6206
Domestic nonprofit research organization
Abstract
In sustained military operations involving round-the-clock missions and travel around the globe, biomathematical models of human performance have potential as tools for predicting the fatigue and performance of sleep-deprived soldiers. This project investigates hybrid neural network/parametric models to address specific gaps in current performance models, identified in the 2002 Fatigue and Performance Modeling Workshop and outlined in the Program Solicitation. This project will follow a conventional life-cycle development protocol where models are systematically developed using novel hybrid techniques, validated, and refined to produce an operationally relevant model. The project's main deliverable will be a proposed algorithm for hybrid neural network/parametric performance prediction in the field given unknown individual trait characteristics and uncertain current state, and a comparative analysis to parametric algorithms.

* information listed above is at the time of submission.

Agency Micro-sites

US Flag An Official Website of the United States Government