Abstract

For applications such as force protection, an effective decision maker needs to maintain an unambiguous grasp of the environment. Opportunities exist to leverage computational mechanisms for the adaptive fusion of diverse information sources. The current research employs neural networks and Markov chains to process information from sources including sensors, weather data, and law enforcement. Furthermore, the system operator's input is used as a point of reference for the machine learning algorithms. More detailed features of the approach are provided, along with an example force protection scenario.

Department(s)

Electrical and Computer Engineering

Report Number

SAND2007-6058

Document Type

Report - Technical

Document Version

Final Version

File Type

text

Language(s)

English

Rights

© 2007 United States. Department of Energy, All rights reserved.

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