改进的Apriori数据挖掘算法的应用  

The Application of an Improved Apriori Algorithm

作　　者：康敏旸[1] 张安[1] 

机构地区：[1]西北工业大学电子信息学院,陕西西安710072

出　　处：《火力与指挥控制》2009年第10期111-114,共4页Fire Control & Command Control

基　　金：航空科学基础基金(05D53021);陕西省自然科学基金资助项目(2006F45)

摘　　要：Apriori算法是一种最有影响的挖掘布尔关联规则频繁项集的基本算法。针对防区外联合攻击武器系统在仿真过程中产生的大量数据,利用Apriori算法对仿真结果进行分析,得出一些有参考价值的规则,实现了关联规则挖掘在军用系统仿真中的应用。并对Apriori算法存在的问题进行了一些改进,用新的修剪策略,提高了算法的效率;增加独立性检验,进一步保证了关联规则的正确性。Apriori is an influential algorithm for mining frequent itemsets for Boolean association rules. To deal with massive data in the standoff missile weapon system, we made use of Apriori algorithm to analysis the result of simulation and generalize some useful rules. Therefore, the association rules mining can be widely used in military simulation of weapon systems. Besides, an improved algorithm based on Apriori algorithm was given, which not only can improve efficiency by a new finding method but also ensure the concision of rules by independent.

关 键 词：防区外联合攻击武器系统 关联规则 APRIORI算法改进 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]