In this study we apply the knowledge of fuzzy sets to group structures and also to decision-making implications. We study fuzzy subgroups of finite abelian groups. We set G = Zpn + Zqm . The classification of fuzzy subgroups of G using equivalence classes is introduced. First, we present equivalence relations on fuzzy subsets of X, and then extend it to the study of equivalence relations of fuz...

Fuzziness is not a priori an obvious concept and demands some explanation. “Fuzziness” is what Black (NF 1937) calls “vagueness” when he distinguishes it from “generality” and from “ambiguity.” Generalizing refers to the application of a symbol to a multiplicity of objects in the field of reference, ambiguity to the association of a finite number of alternative meanings having the same phonetic...

This paper presents a new approach using fuzzy bet theory for voltage and reactive power control of power systems. The predication of steady state voltage stability conditions in a transmission network. The voltage stability is checked by formulating an L and the corresponding uncertainties input parameters are efficiently modeled in terms of fuzzy sets by using triangular membership function. ...

A system for evaluating land suitability using fuzzy logic method has been developed. The system determining a degree of delimitation, land ratings, suitability classes, and their actual land suitability subclasses of given land characteristics. The main parts of the evaluation process, which included in the fuzzy inference engine of the knowledge based system, are fuzzification and defuzzifica...

A new scheme to obtain optimal fuzzy subsets and rules is proposed. The method is derived from the use of genetic algorithms, where the genes of the chromosome are classified into two different types. These genes can be arranged in a hierarchical form, where one type of genes controls the other type of genes. The effectiveness of this genetic formulation enables the fuzzy subsets and rules to b...

This paper reports the use of simulated annealing to design more efficient fuzzy logic systems to model problems with associated uncertainties. Simulated annealing is used within this work as a method for learning the best configurations of interval and general type-2 fuzzy logic systems to maximize their modeling ability. The combination of simulated annealing with these models is presented in...

This paper is an attempt to introduce a new framework to handle both uncertainty and time in spatial domain. The application of the fuzzy temporal constraint network (FTCN) method is proposed for representation and reasoning of uncertain temporal data. A brief introduction of the fuzzy sets theory is followed by description of the FTCN method with its main algorithms. The paper then discusses t...

Gupta and Ray (Fuzzy Sets and Systems 54 (1993) 191) introduced the notion of fuzzy projective planes. We show that an old theorem of Dembowski classi$es all $nite fuzzy projective planes, that the examples in Gupta and Ray (Fuzzy Sets and Systems 54 (1993) 191) arise from ordinary projective planes and have much easier descriptions that can easily be generalized, and that there exist fuzzy pro...