Establishing a Data-Mining Environment for Wartime Event Prediction with an Object-Oriented Command and Control Database

This paper documents progress to date on a research project, the goal of which is wartime event prediction. The paper describes the operational concept, the datamining environment, and the data-mining techniques that use Bayesian networks for classification. Key steps in the research plan are (1) implement machine learning, (2) test the trained networks, and (3) use the technique to support a battlefield commander by predicting enemy attacks. Data for training and testing the technique can be extracted from the object-oriented database that supports the Integrated Marine Multi-Agent Command and Control System (IMMACCS). The class structure in the IMMACCS data model is especially well suited to support attack classification. Establishing a Data-Mining Environment for Wartime Event Prediction with an Object-Oriented Command and Control Database