Fuzzy data mining is used to extract fuzzy knowledge from linguistic or quantitative data. It is an extension of traditional data mining and the derived knowledge is relatively meaningful to human beings. In the past, we proposed a mining algorithm to find suitable membership functions for fuzzy association rules based on ant colony systems. In that approach, precision was limited by the use of...

In this paper we upgraded the Luhandjula’s method (Fuzzy Sets and Systems, 13(1), (1984), 11-23) for multiple objective linear plus fractional programming problems (MOL+FPP) with modification given by Dutta et al. (Fuzzy Sets and System, 52(1), (1992), 39-45). The aim of this paper is to show new fuzzy set approach for MOL+FPP by defining new membership function for linear function part and si...

abstract drought is a natural creeping event that starts due to lower moisture compared to normal condition. this phenomenon impacts all aspects of human activities. however there is neither any detailed definition nor a general and proper index for drought monitoring. in this study, fuzzy logic has been applied to deal with inherent uncertainties of the real world data. we presented a fuzzy mo...

A new fuzzy filter is presented for the noise reduction of images corrupted with additive noise. The filter consists of two stages. The first stage computes a fuzzy derivative for eight different directions. The second stage uses these fuzzy derivatives to perform fuzzy smoothing by weighting the contributions of neighboring pixel values. Both stages are based on fuzzy rules which make use of m...

A novel method is presented for mining fuzzy association rules that have a temporal pattern. Our proposed method contributes towards discovering temporal patterns that could otherwise be lost from defining the membership functions before the mining process. The novelty of this research lies in exploring the composition of fuzzy and temporal association rules, and using a multi-objective evoluti...

In this paper, pretopological and topological operators are introduced based on partially continuous linear transformations of the membership and non-membership functions for intuitionistic fuzzy sets. They turn out to be a generalization of the topological operators for intuitionistic fuzzy sets.On the other hand it is a generalization of the fuzzy set pretopological operators introduced...

Fuzzy Logic Controllers are knowledge-based systems, incorporating human knowledge into their Knowledge Base through Fuzzy Rules and Fuzzy Membership Functions. The deenition of these Fuzzy Rules and Fuzzy Membership Functions is generally aaected by subjective decisions, having a great innuence over the performance of the Fuzzy Controller. In some cases, the Membership Functions are deened wit...

Evolutionary learning and especially genetic optimisation algorithms have recently received a lot of research attention as tools for identifying fuzzy models of the systems. Most often fuzzy modelling employ the fuzzy IF–THEN rules. In this paper, besides AND–operator the OR–operator is also considered in constructing the premise rule base. A genetic algorithm is utilised to find the premise st...