This paper is focused on studying how data privacy could be preserved with fuzzy rule bases as interpretable as possible. These fuzzy rule bases are obtained from a data mining strategy based on building a decision tree. The antecedents of each rule produced by these systems contain information about the released variables (quasiidentifier) whereas the consequent contains information only about...

Multiple-criteria decision-making (MCDM) that deals with multiple criteria in decision-making environments has been explicitly applied to various decision-making fields. Nevertheless, the critical issues of uncertainty and inaccuracy generally and gradually exists in the majority of the MCDM processes because of (1) prejudice and preference of decision-makers or experts as well as (2) the insuf...

Multiple-criteria decision-making (MCDM) that deals with multiple criteria in decision-making environments has been explicitly applied to various decision-making fields. Nevertheless, the critical issues of uncertainty and inaccuracy generally and gradually exists in the majority of the MCDM processes because of (1) prejudice and preference of decision-makers or experts as well as (2) the insuf...

We develop some new cases of the induced continuous ordered weighted averaging (ICOWA) operator and study their desirable properties, which are very suitable to deal with group decision making (GDM) with interval fuzzy preference relations. First, we present the consensus indicator ICOWA (CI-ICOWA) operator which uses the consensus indicator of the interval fuzzy preference as the order inducin...

The use of unsupervised fuzzy learning classifications techniques allows defining innovative classifications to be applied on marketing customer’s segmentation. Segmenting the clients’ portfolio in this way is important for decision-making in marketing because it allows the discovery of hidden profiles which would not be detected with other methods. Different strategies can be established for e...

In this research we concentrate on developing a bifuzzy model for a Single-period inventory problem. The conventional studies have focused on the cases that the demands are probabilistic and follow certain distribution function; or the demands are considered as fuzzy variables; or the demands is expressed by random fuzzy variable. Recently, fuzzy random variables have been applied to some decis...

Multi-objective inventory models of deteriorating items have been developed with vague and imprecise information about available storage area. Here, the objectives are (i) to maximize the profit, (ii) to minimize the wastage cost due to deterioration and (iii) to minimize the total production cost. These objectives are also fuzzy in nature. In these models, production rate is a decision variabl...

Most decision making problems can be considered as multiple criteria decision making (MCDM) problems, and should be solved by MCDM method. The main advantage of MCDM is that it can give managers many dimensions to consider related elements, and evaluate all possible options under variable degrees. This paper applied fuzzy set theory and a compromised MCDM method VIKOR method to evaluate the ser...

This paper introduces adaptive fuzzy equalizers with variable step size for broadband power line (PL) communications. Based on delta-bar-delta and local Lipschitz estimation updating rules, feedforward, and decision feedback approaches, we propose singleton and nonsingleton fuzzy equalizers with variable step size to cope with the intersymbol interference (ISI) effects of PL channels and the ha...

fuzzy decision tree (fdt) classifiers combine decision trees with approximate reasoning offered by fuzzy representation to deal with language and measurement uncertainties. when a fdt induction algorithm utilizes stopping criteria for early stopping of the tree's growth, threshold values of stopping criteria will control the number of nodes. finding a proper threshold value for a stopping crite...