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http://dx.doi.org/10.9766/KIMST.2014.17.6.773

A Non-Kinetic Behavior Modeling for Pilots Using a Hybrid Sequence Kernel  

Choi, Yerim (Department of Industrial Engineering, Seoul National University)
Jeon, Sungwook (Department of Industrial Engineering, Seoul National University)
Jee, Cheolkyu (The 7th Research and Development Institute, Agency for Defense Development)
Park, Jonghun (Department of Industrial Engineering, Seoul National University)
Shin, Dongmin (Department of Industrial and Management Engineering, Hanyang University)
Publication Information
Journal of the Korea Institute of Military Science and Technology / v.17, no.6, 2014 , pp. 773-785 More about this Journal
Abstract
For decades, modeling of pilots has been intensively studied due to its advantages in reducing costs for training and enhancing safety of pilots. In particular, research for modeling of pilots' non-kinetic behaviors which refer to the decisions made by pilots is beneficial as the expertise of pilots can be inherent in the models. With the recent growth in the amount of combat logs accumulated, employing statistical learning methods for the modeling becomes possible. However, the combat logs consist of heterogeneous data that are not only continuous or discrete but also sequence independent or dependent, making it difficult to directly applying the learning methods without modifications. Therefore, in this paper, we present a kernel function named hybrid sequence kernel which addresses the problem by using multiple kernel learning methods. Based on the empirical experiments by using combat logs obtained from a simulator, the proposed kernel showed satisfactory results.
Keywords
Non-Kinetic Behavior Modeling; Pilots; Hybrid Sequence Kernel; Combat Logs; Support Vector Machines;
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Times Cited By KSCI : 3  (Citation Analysis)
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