Application of Associate Rules Mining on CGFs Behavior Modeling
In this paper, Computer Generated Forces (CGF) behavior modeling was studied from the viewpoint of associate data mining, for the large quantity of data, rules and models in its process. Because CGF behavior models data source was the combination of staticDB and dynamic data stream, the paper advanced the methods of item truncation and aim-pattern restriction. Through pretreatment, coding, searching frequent pattern, generating associate rules of the CGF behavior modeling data, then decision could be made according as these rules. Application of the two methods improves on the classical aprior algorithm, also improves efficiency of searching frequent items and credibility of CGFs decision. Finally, the application of associate rules mining in air-combat is studied in detail. As the simulation shows, comparing with the traditional matching-rule decision, associate rule mining has higher efficiency on condition with guaranteeing reliability of decision.
CGF data mining behavior modeling aircombat associate rules mining
Gong Jianglei Gong Guanghong Song Xiao
Advanced Simulation Technology Aviation Science and Technology Key Laboratory Beihang University Beijing China
国际会议
太原
英文
279-283
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）