基于双向概念格的坦克驾驶模拟训练关联规则挖掘

doi:10.3969/j.issn.1000-1093.2020.12.004

摘要/Abstract

摘要： 利用坦克驾驶模拟器进行模拟训练是提高装备操作技能的重要方法。针对以往模拟训练采用统计分析方法难以从复杂训练数据中发现知识和规律的不足，提出基于双向概念格的关联规则挖掘方法，对坦克驾驶模拟训练结果进行分析。采用矩阵布尔化操作将原始数据表转化为单值形式背景，完成对坦克驾驶模拟训练多值数据处理；定义内涵秩和外延秩，实现从概念格的顶层、底端双向搜索概念节点，同时结合支持度阈值约简冗余节点；设计规则后件固定作为约束条件，过滤不相关的频繁项集，提取满足用户挖掘目标的关联规则。实验结果表明，基于双向概念格的关联规则挖掘方法在运行时间和生成频繁项集上有明显优势，将其应用于某型坦克驾驶模拟器的训练结果分析中，提取了有价值的约简关联规则，进一步验证了该方法的可行性与有效性。

关键词: 坦克, 驾驶模拟器, 双向概念格, 关联规则, 模拟训练

Abstract: Training by tank driving simulator is an important way of improving the operating skill of equipment. The statistical analysis method is difficultly used to find the knowledge and rules from the complex training data in simulation training. A mining method of association rules based on bidirectional concept lattice is proposed to analyze the simulation training results of tank driving. The original data table is transformed into single value formal background by using Boolean matrix operation to complete the multiple value data processing of tank driving simulation training. Connotative rank and denotative rank are defined to search the concept nodes from the top and bottom of concept lattice, and the redundant nodes are reduced by combining the support thresholds. Post rule is designed as constraint condition to filter the irrelevant frequent item set, and extract the association rules that meet the mining target of users. The experimental results show that the association rules mining method based on bidirectional concept lattice has obvious advantages in run time and generating frequent item set. It is applied to analyze the training results of a tank driving simulator to extract the valuable reduction association rules, which further verifies the feasibility and effectiveness of the method.

Key words: tank, drivingsimulator, bidirectionalconceptlattice, associationrule, simulationtraining

中图分类号:

邓青, 薛青, 高恒, 翟凯. 基于双向概念格的坦克驾驶模拟训练关联规则挖掘[J]. 兵工学报, 2020, 41(12): 2397-2407.

DENG Qing, XUE Qing, GAO Heng, ZHAI Kai. Mining Association Rules of Tank Driving Simulation Training Based on Bidirectional Concept Lattice[J]. Acta Armamentarii, 2020, 41(12): 2397-2407.

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