In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algorithms in dealing with the challenges posed by large collections of vague and uncertain natural data. This paper reviews concept of fuzzy logic and fuzzy clustering. The classical fuzzy c-means algorithm is presented and its limitations are highlighted. Based on the study of the fuzzy c-means algor...

In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algorithms in dealing with the challenges posed by large collections of vague and uncertain natural data. This paper reviews concept of fuzzy logic and fuzzy clustering. The classical fuzzy c-means algorithm is presented and its limitations are highlighted. Based on the study of the fuzzy c-means algor...

New trends and the effect of key factors influence the quality of the holes produced by ECM processes. Researchers developed a fuzzy logic controller by adding intelligence to the ECM process. Maintaining optimum ECM process conditions ensures higher machining efficiency and performance. This paper presents the development of a fuzzy logic controller to add intelligence to the ECM process. An e...

Fuzzy Logic is a framework particularly useful to formalise and deal with imprecise concepts and statements expressed in natural language. This paper has three related aims: 1. To provide a short introduction to the basics of Fuzzy Logic within the context of social simulation. 2. To present and disseminate a well-documented NetLogo extension that facilitates the use of Fuzzy Logic within NetLo...

This contribution addresses the generation of textual descriptions in several natural languages for evaluation of human behavior in video sequences. The problem is tackled by converting geometrical information extracted from videos of the scenario into predicates in fuzzy logic formalism, which facilitates the internal representations of the conceptual data and allows the temporal analysis of s...

the idea of this paper is designing an automatic fault detection system based on fuzzy logic, therefore two signals of pmsm in fault condition are analyzed for inter turn fault detection: current and torque. in this fault type there is some distortion in these signals, but it is not good enough to detecting with fuzzy logic solely, so with combination of wavelet transform and fcm a new method f...

The main idea motivating the development of fuzzy logic (FL) can be formulated as follows: Fuzzy logic is a special many-valued logic addressing the vagueness phenomenon and developing tools for its modeling via truth degrees taken from an ordered scale. It is expected to preserve as many properties of classical logic as possible. During the past 15 years, the mathematical FL has been developed...

In this paper we will investigate which fuzzy/linguistic rules are redundant in systems of such rules called linguistic descriptions. We present a formal definition of redundancy and show that rules which are seemingly redundant can be in fact indispensable. These results apply for IF-THEN rules which use evaluative linguistic expressions (e.g., small, very big, etc.) and inference method calle...

during recent years several attempts have been made to incorporate environmental and natural resources degradation into national accounts. gnp as measured by the traditional system of national accounts does not consider environmental degradation caused by inefficient exploitation of natural resources. while the complete omission of environmental impacts is not possible, there could be an optima...

A natural interpretation of GUHA style data mining logic in paraconsistent fuzzy logic framework is introduced. Significance of this interpretation is discussed.