An efficient spatial high-utility occupancy frequent item mining algorithm for mission system integration architecture design using the MBSE method
Tóm tắt
Future airspace operations require the integration of various types of comprehensive combat forces, which belong to systematic combat. At present, integrated systems are oriented to the single platform system. Systematic integrated mission system is more complex, which not only considers the utility and efficiency of the single platform, but also considers multi-platform collaboration. Therefore, it is more complicated and difficult to obtain requirements and design mission system architecture, which requires multiple design scenarios. Due to the large amount of data of the scenarios model, the efficiency of manual analysis is too low, so data mining method is needed to analyze the scenarios data. However, traditional data mining methods cannot simultaneously mine item location information and utility occupancy. This paper proposes an algorithm: SHUO-FI, to mine utility occupancy threshold under specified distance constraints and a new pruning strategy based on support and maximum utility occupancy constraints. Compared with other algorithms, it is found that the proposed algorithm has higher efficiency. Since the algorithm considers the location, weight, profit, utility and other parameters of the project, it can be better applied in the field of forward design MBSE than the previous algorithm. Finally, the algorithm is applied to the actual coordination of manned and unmanned aircraft model. By data mining the utility, profit and real-time position of each operational unit at each time, the optimal operational function scheduling mode under the same operational mission can be obtained.
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