The similarity measure of fuzzy numbers is very important in many research fields such as pattern recognition [[5],[6]] and risk analysis in fuzzy environment [[1],[3],[15]]. Some methods have been presented to calculate the degree of similarity between fuzzy numbers [[1][4],[8],[15]]. In [16], Wen presented A modified similarity measure of generalized fuzzy numbers. Pandey et al.,[7] proposed ...

Fuzzy systems have been used in many fields like data mining, regression, patter recognition, classification and control due to their property of handling uncertainty and explaining the property of complex system without involving a specific mathematical model. Fuzzy rule based systems (FRBS) or fuzzy rule based classifiers (particularly designed for classification purpose) are basically the fu...

A fuzzy decision tree is an important tool for knowledge acquisition in uncertain environments. Most of the existing fuzzy decision tree algorithms do not systematically consider the impact of the non-linear characteristics of the membership degree of fuzzy sets; they are therefore unable to integrate uncertainty processing preferences into the selection of extended attributes. This paper initi...

with quick development of digital images and the availability of imaging tools, massive amounts of images are created. therefore, efficient management and suitable retrieval, especially by computers, is one of themost challenging fields in image processing. automatic image annotation (aia) or refers to attaching words, keywords or comments to an image or to a selected part of it. in this paper,...

annihilation or reduction of each kind of noise blended in correct data signals is a field that has attracted many researchers. it is a fact that fuzzy theory presents full capability in this field. fuzzy filters are often strong in smoothing corrupted signals, whereas they have simple structures. in this paper, a new powerful yet simple fuzzy procedure is introduced for sharpness reduction in ...

This paper proposes a new topic in substructural logic for use in research joining the fields of relevance and fuzzy logics. For this, we consider old and new relevance principles. We first introduce fuzzy systems satisfying an old relevance principle, i.e., Dunn’s weak relevance principle. We present ways to obtain relevant companions of the weakening-free uninorm (based) systems introduced by...

PROMETHEE refers to a collection of methods of ranking in the field of multi-criteria decision making. These methods are characterized by conceptual simplicity and practical applicability. However, the nature of phenomena involving decision-making in real world leads us to use fuzzy method of preference ranking. The most common criticism on mathematical ranking procedures is that they tend to d...

Description logics (DLs) are a family of well-studied knowledge representation formalisms designed to express and reason with the conceptual knowledge of application domains in a clear and well-understood manner. They have been successfully applied for representing large application domains, most prominently from the biological and medical fields. In their classical form, DLs are not adequate f...

This paper mainly deals with the design of forecasting model for Hydro power generation using Fuzzy time series. The fuzzy time series has recently received an increasing attention because of its capability of dealing with vague and incomplete data. There have been a variety of models developed either to improve forecasting accuracy or reduce computation overhead. This technique has been applie...

This work presents a high resolution image classification by generating binary random fields based on fuzzy semantic rules by means of descriptors such as form, texture and relations between objects and sub-objects. Fuzzy systems are capable of representing diverse, non exact, uncertain and inaccurate knowledge or information. They use qualifiers that are very close to the human way of expressi...