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

Award Information
Agency: Department of Defense
Branch: Army
Contract: W81XWH-05-C-0155
Agency Tracking Number: A054-029-0337
Amount: $99,998.00
Phase: Phase I
Program: STTR
Awards Year: 2005
Solicitation Year: 2005
Solicitation Topic Code: A05-T029
Solicitation Number: N/A
Small Business Information
PULSAR INFORMATICS, INC.
1 Old Dominion University, Norfolk, VA, 23529
DUNS: 158273743
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Daniel Mollicone
 President
 (215) 520-2630
 dan@pulsarinformatics.com
Business Contact
 Daniel Mollicone
Title: President
Phone: (215) 520-2630
Email: 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.

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