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.
T. Draelos et al., "Coordinated Machine Learning and Decision Support for Situation Awareness,", pp. 1-46 United States. Department of Energy, Jan 2007.
The definitive version is available at http://dx.doi.org/10.2172/920460
Electrical and Computer Engineering
Report - Technical
© 2007 United States. Department of Energy, All rights reserved.