A SPATIO-TEMPORAL BACKPROPAGATION NEURAL NETWORK APPROACH TOFISHERY STOCK PREDICTION

Award Information
Agency: Department of Commerce
Branch: N/A
Contract: N/A
Agency Tracking Number: 17464
Amount: $34,775.00
Phase: Phase I
Program: SBIR
Awards Year: 1992
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
6811 Kenilworth Ave, Suite 306, Riverdale, MD, 20737
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Dr. Srinivasan Raghavan
 () -
Business Contact
Phone: () -
Research Institution
N/A
Abstract
THE PRIMARY OBJECTIVE OF THIS PROPOSAL IS TO DESIGN AND BUILD A SYSTEM FOR FISHERY AND MARINE MAMMAL STOCK PREDICTION USING NONLINEAR SPATIO-TEMPORAL NEURAL NETWORK THEORY. WHILE THE CENTRAL ENGINE OF THE SYSTEM MAKES USE OFNONLINEAR NEURAL NETWORKS FOR PREDICTION, SEVERAL PERIPHERAL MODULES INCORPORATED IN THE DESIGN ASSIST THE USER IN EMPLOYING THE PREDICTOR FOR VARIOUS APPLICATIONS. IN PARTICULAR, OUR APPROACH INVOLVES A USER-FRIENDLY EXPERT SYSTEM AT THE FRONT END TO INTERACT WITH THE USER ON THE DATA DOMAIN, WHILE A RECONFIGURABLE NONLINEAR NEURAL NETWORKFORMS THE CRUX OF A PROBLEM SOLVING SYSTEM. NEURAL NETWORKSHAVE PROVENLY OUTPERFORMED TRADITIONAL LINEAR AND OTHER STATISTICAL PREDICTORS IN THE PAST FOR VARIOUS APPLICATIONS,INCLUDING ENERGY DEMAND PREDICTION (WERBOS 1988). ONE OF THE INHERENT DIFFICULTIES WITH THEM IS THEIR INABILITY TO "EXPLAIN" TO THE USER THEIR DECISIONS. OUR CHOICE OF EXPERTSYSTEMS TO INTERACT WITH THE USER IS WARRANTED BECAUSE OF THE USER-FRIENDLY NATURE OF NATURAL LANGUAGE TYPE INTERACTIONS THAT USERS ARE COMFORTABLE WITH. HENCE AN EXPERT-NEURAL NETWORK PREDICTOR.

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

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