In this paper, we present a multistage genetic learning process for obtaining linguistic fuzzy rule-based classification systems that integrates fuzzy reasoning methods cooperating with the fuzzy rule base and learns the best set of linguistic hedges for the linguistic variable terms. We show the application of the genetic learning process to two well known sample bases, and compare the results...

The aim of this paper is to propose a procedure to estimate missing preference values when dealing with incomplete fuzzy linguistic preference relations assessed using a 2–tuple fuzzy linguistic approach. This procedure attempts to estimate the missing information in an individual incomplete fuzzy linguistic preference relation using only the preference values provided by the respective expert....

In this study an academician selection system has been developed for universities using fuzzy weighting and fuzzy ranking. In the system, effects of many criteria and views of many experts are evaluated for selection. Number of criteria, number of linguistic variables of criteria, names of linguistic variables, membership functions of linguistic variables, number of experts and alternatives can...

A new method is proposed to solve the multiple attribute decision making (MADM) problems with the trapezoid fuzzy linguistic variables ( Vs TFL ) based on the trapezoid fuzzy linguistic hybrid harmonic averaging (TFLHHA ) operator. To begin with, this paper reviews the concept and operational rules of the Vs TFL , the calculation method of the possibility degree with Vs TFL , and the comparison...

A neural fuzzy system learning with linguistic teaching signals is proposed in this paper. This system is able to process and learn numerical information as well as linguistic information. It can be used either as an adaptive fuzzy expert system or as an adaptive fuzzy controller. At first, we propose a fivelayered neural network for the connectionist realization of a fuzzy inference system. Th...

We study the multi-attribute group decision making (MAGDM) problems in which the attribute values provided by the decision makers take the form of intuitionistic trapezoid fuzzy linguistic (ITrFL) information considering the uncertainty and inaccuracy of input arguments. Some new aggregation operators called intuitionistic trapezoid fuzzy linguistic weighted average (ITrFLWA), intuitionistic tr...

We present a neuro-fuzzy system for character recognition from printed documents using a fuzzy Hough transform technique. For each character pattern, fuzzy Hough transform extracts information from the standard Hough transform accumulator cells into a number of fuzzy sets. These basic fuzzy sets are combined by t-norms to synthesize additional fuzzy sets whose heights form an n-dimensional feat...

The aim of fuzzy risk analysis is to evaluate the probability of failure of every component consisting of many sub-components and the probability of failure is the combination of estimations of severity of loss and probability of failure of sub-components which are vaguely known. In this paper, we present a new method for fuzzy risk analysis with linguistic evaluating values. Firstly, we propos...

We recall the concept of a linguistic variable and the representation of its values (i.e. linguistic terms) by means of fuzzy sets. In this framework adverbs are represented by fuzzy modifiers, i.e. operators acting on these fuzzy sets. We investigate two important classes of popular fuzzy modifiers. Grounding on results from psycholinguistic research, we discuss their pro’s and contra’s for re...

This paper gives a short introduction into Fuzzy Set Theory, presents an overview on fuzzy controllers, and discusses possible combinations between fuzzy controllers and neural networks. Fuzzy Sets suggested by L.A. Zadeh 32] ooer a possibility to formally describe linguistic expressions like tall, fast, medium, etc., and to operate on them. Fuzzy controllers use fuzzy sets to represent linguis...