Decision makers are often faced with several conflicting alternatives. How do they evaluate
trade-offs when there are more than three criteria? To help people make optimal decisions …

The inductive learning of fuzzy rule-based classification systems suffers from exponential
growth of the fuzzy rule search space when the number of patterns and/or variables …

The objective of inventory management is to make decisions regarding the appropriate level
of inventory. In practice, all inventories cannot be controlled with equal attention. The most …

When people or computers need to make a decision, typically multiple conflicting criteria
need to be evaluated; for example, when we buy a car, we need to consider safety, cost and …

The main aim of this paper is to present a revision of the most relevant results about the use
of Fuzzy Sets in Data Mining, specifically in relation with the discovery of Association Rules …

Fuzzy rule-based classifiers have been used in many applications showing better
performance due to simple modular architectures and significant interpretability. Generally …

In order to get a more general result related on fuzzy implications that induced by
aggregation functions, we relax the definition of general overlap functions, more precisely …

In fuzzy rule-based classification systems (FRBCSs), rule weighting has often been used as
a simple mechanism to tune the classifier. In past research, a number of heuristic rule weight …

Classification is one of the most popular data mining techniques applied to many scientific
and industrial problems. The efficiency of a classification model is evaluated by two …

Association rule mining is an important data analysis method for the discovery of
associations within data. There have been many studies focused on finding fuzzy …