Research And Application Of Fuzzy Association Rule Mining Algorithm

With the intensification and development of the new military innovation, information technologies arouse the rapid increase of data, military transform has to be happened via information processing technology such as data mining.Data mining is powerful tool for getting an informationize advantage and seizing the initiative in the informationize war in the future. At the arming support system,the arming maintenance materials are the important elements of the arming maintenance support,have an effect on the integrality and performance of arming. With the increasing complexity of arming, the choice and optimizing of maintenance materials become more and more important. Discovering the rules of maintenance materials using is signality for the optimizing decision-making,and can improve the efficiency of arming maintenance materials support. As one of the main tasks in the field of data mining,association rule mining is used to discover the relationships among the attributes,and it is a useful approach to address the problem of optimizing maintenance materials support.Based on the research of association rule mining algorithm and considering the feature of the problem, this thesis puts the research attention to one of the association extend forms——fuzzy association rule. In order to improve the efficiency of existing fuzzy association rule mining algorithm, we proposed a mining algorithm base on linear linklist in this thesis via learning the merits of the classic association rule mining algorithm Apriori and FP-tree. This algorithm scans database once, and only records the information of the transactions, which are useful for counting the support of the frequent itemset. It reduces the spending of data storage, increase the running efficiency. We prove this algorithm has high performance via the time complexity analysis. We also have tested the veracity and validity of this algorithm by experiment on a dataset from UCI. And last,we use this algorithm to solve the optimizing problem of maintenance materials support.In this thesis, we first use fuzzy association rule minimg method to solve the optimizing problem of maintenance materials support, propose a excellent mining algorithm, and build the mining modeling via using a data mining methodology called CRISP-DM. It is a valuable reference for arming maintenance materials support for our army.