A novel approach is proposed in order to get better utilization of the current method for quantitative analysis of military simulated situations during simulation-based combat systems R&D. We argue that this approach increases the usability of the data that is being collected from the simulation, and enables the simulation researchers to find unrevealed data that hardly could be found using trivial methods. For example, the unrevealed information could be recognizing hidden human factors (behavioral patterns) and recognizing irregular events occurring during the simulation. This paper describes the present analysis method, the need for better analysis tools and methods, the proposed broadened method for experiment data analysis, the challenges in using this approach, and the phases that should be added to the current methodology.
Broadening Quantitative Analysis of Distributed Interactive Simulation With Data Mining Functionalities
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