Fuzzy Association Rule Mining And Its Applications

With the development of information technology, Data Mining has been paid attention extensively. As we know, Data Mining has a large research scope, Association rules mining is one of the important research and the most active research methods subject in it. Deeply researching into the subject has the most important values not only in theory,but also in applications. Association rule mining is put forward by Agrawal and the others in1993, Firstly be proposed for market basket analysis problem and the purpose is analyzing the relation of items in transaction database, later, researchers improved and extended the prototype of the question. At present, association rules technology has been applied in business, telecommunication, finance, agriculture, medical treatment and so on. It has brought a good effect.The main work of the thesis is:1. On the basic of the research and summary about fuzzy association rule problem, To classify the existing association rule mining model, In-depth analysis and discussion of some typical fuzzy association rules mining model. I pointed out the problem of mining fuzzy association rules existing deficiencies.2. Against quantity of fuzzy association rules, I propose a new form of the definition of support (the introduction of regulatory factorα), construct a new fuzzy association rule mining model.3. Combined with Boolean association rules generation algorithm, on this basis, a new algorithm for mining fuzzy association rules is proposed.4. we combine with the practical case of evaluation on electromagnetic environment for a few pre-selection stations before constructing civil aviation airport, improve original methods, excavate the attribute information which infects evaluation on electromagnetic environment of airport, and propose a method based on fuzzy association rule.