Aiming at high overshoot and steady-state error in fuzzy controller of underwater vehicles, a new method based on data mining technique was presented. Apply Boolean association rule data mining to mine the polling list of fuzzy control from the database of manual operation record, and simulation and outfield experiments were carried out on Super Mohawk underwater vehicle to verify the feasibili...

Mining hybrid dimension fuzzy association rule is one of the important processes in data mining . Apriori algorithm concerned with handling single level, single dimensional association rules. this paper is presenting, a new modification in joining process to reduce the redundant generation of sub items during pruning the candidate itemsets, which can obtain higher efficiency of mining that of o...

In this paper we present how to extract fuzzy association rules involving both the presence and the absence of items using a fuzzy rule mining procedure introduced by the authors in previous works. The rule mining procedure is based on the GUHA logical model, fuzzified via a recently proposed representation of gradualness. We present some results obtained with real datasets.

Modern medicine generates a great deal of information stored in the medical database. Extracting useful knowledge and providing scientific decision making for the diagnosis and treatment of disease from the database increasingly becomes necessary. In India most of the people suffering cancer diseases. Using association rule mining for constructing classification system for diagnosing cancer dis...

One of the most well-known and extended data mining techniques is that of association rule mining, a helpful tool to discover relations between items present in sets of transactions. Nevertheless, in some other scenarios, another interesting issue is that of considering not only the possible relations involving presence of items, but the absence of them. The problem gets more complex when it is...

Data mining methods including association rule mining and frequent episode mining have been applied to the intrusion detection problem. In other work, we have introduced modifications of these methods that mine fuzzy association rules and fuzzy frequent episodes and have described off-line methods that utilize these fuzzy methods for anomaly detection from audit data. In this paper we describe ...

The problem of mining association rules in a database are introduced. Most of association rule mining approaches aim to mine association rules considering exact matches between items in transactions. A new algorithm called ―Without expert fuzzy based data mining Based on Fuzzy Similarity to mine new Association Rules ‖ which considers not only exact matches between items, but also the fuzzy sim...

finding frequent patterns plays a key role in exploring association patterns, correlation, and many other interesting relationships that are applicable in tdb. several association rule mining algorithms such as apriori, fp-growth, and eclat have been proposed in the literature. fp-growth algorithm construct a tree structure from transaction database and recursively traverse this tree to extract...