We describe an interactive method to generate a set of fuzzy clusters for classes of interest of a given, labeled data set. The presented method is therefore best suited for applications where the focus of analysis lies on a model for the minority class or for smallto medium-size data sets. The clustering algorithm creates one-dimensional models of the neighborhood for a set of patterns by cons...

7 0 9 0 | P a g e c o u n c i l f o r I n n o v a t i v e R e s e a r c h M a y 2 0 1 6 w w w . c i r w o r l d . c o m An Optimization Method Using Clustering Technique for the Human Emotions Detection Artificial Neuro-Fuzzy Logic System Omayya Murad, Mohammed Malkawi 1 st The University Of Jordan, Amman Jordan, [email protected] 2 nd Associate Professor at JUST, Irbid, Jordan, mimalkawi@...

This research focused on measuring perceived quality in the context of sport and fitness services using a novel approach in sport management: fuzzy logic. Several analytical procedures have been depicted to operate with fuzzy techniques, which may be applied to empirical research by a wide range of researchers in the sport literature, as well as sport managers. This study showed that fuzzy logi...

In formal concept analysis of data with fuzzy attributes, both the extent and the intent of a formal (fuzzy) concept may be fuzzy sets. In this paper we focus on so-called crisply generated formal concepts. A concept 〈A,B〉 ∈ B (X,Y, I) is crisply generated if A = D↓ (and so B = D↓↑) for some crisp (i.e., ordinary) set D ⊆ Y of attributes (generator). Considering only crisply generated concepts ...

General fuzzy association rules mining focuses on finding out the fuzzy itemsets or fuzzy attributes which frequently occur together. But two fuzzy itemsets which frequently occur together can not imply that there is always an interesting relationship between them. In this paper, we develop an alternative framework for mining interesting relationship between fuzzy itemsets based on fuzzy correl...

In order to analyze vague data set of uncertainty information, Fuzzy Formal Concept Analysis(FFCA) incorporates fuzzy set theory into Formal Concept Analysis(FCA). It extracts useful information with a unit of fuzzy concept from given fuzzy formal context with a confidence threshold. Then it constructs fuzzy lattice by order relations between the fuzzy concepts. In this paper, we introduce basi...

one-way analysis of covariance is a popular and common statisticalmethod, wherein the equality of the means of several random variables whichhave a linear relationship with a random mathematical variable, is tested. inthis study, a method is presented to improve the one-way analysis of covari-ance when there is an uncertainty in accepting the statistical hypotheses. themethod deals with a fuzzy...

This paper provides a detailed analysis of fuzzy point, fuzzy line segment, fuzzy distance and the angle between two fuzzy line segments. Two new concepts, same points and inverse points, are defined for this analysis. The basic properties of fuzzy distance, ideas about the containment of a fuzzy point on a fuzzy line segment and the coincidence of two fuzzy points are also described. A linear ...