Fuzzy logic is an organized and mathematical method of handling inherently imprecise concepts through the use of membership functions, which allows membership with a certain degree. It has found application in numerous problem domains. It has been used in the interval [0, 1] fuzzy clustering, in pattern recognition and in other domains. In this paper, we introduce fuzzy logic, fuzzy clustering and an application and benefits. A case analysis has been done for various clustering algorithms in Fuzzy Clustering. It has been proved that some of the defined and available algorithms have difficulties at the borders in handling the challenges posed in collection of natural data. An analysis of two fuzzy clustering algorithms namely fuzzy c-means a...
Abstract. In this paper, we study and improve the fuzzy clustering index and clustering algorithm pr...
The fuzzy clustering algorithm is to classify the data or indicators with a greater degree of simila...
This chapter provides a comprehensive, focused introduction to clustering, viewed as a fundamental m...
The cluster analysis of fuzzy clustering according to the fuzzy c-means algorithm has been described...
Fuzzy logic systems have many applications in every field of moderate science. Most of the fuzzy log...
Provides a timely and important introduction to fuzzy cluster analysis, its methods and areas of app...
In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algori...
Fuzzy clustering algorithms are widely used in many fields, more and more research results have been...
textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has...
Fuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applie...
Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is pro...
Abstract — Clustering is a collection of objects which are similar between them and dissimilar to th...
The paper deals with a special class of cluster analysis methods where a membership degree is calcul...
This paper deals with a new method of fuzzy clustering. The basic concepts of the method are introdu...
A hard partition clustering algorithm assigns equally distant points to one of the clusters, where e...
Abstract. In this paper, we study and improve the fuzzy clustering index and clustering algorithm pr...
The fuzzy clustering algorithm is to classify the data or indicators with a greater degree of simila...
This chapter provides a comprehensive, focused introduction to clustering, viewed as a fundamental m...
The cluster analysis of fuzzy clustering according to the fuzzy c-means algorithm has been described...
Fuzzy logic systems have many applications in every field of moderate science. Most of the fuzzy log...
Provides a timely and important introduction to fuzzy cluster analysis, its methods and areas of app...
In Data mining, Fuzzy clustering algorithms have demonstrated advantage over crisp clustering algori...
Fuzzy clustering algorithms are widely used in many fields, more and more research results have been...
textabstractFuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has...
Fuzzy clustering is a widely applied method for obtaining fuzzy models from data. It has been applie...
Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is pro...
Abstract — Clustering is a collection of objects which are similar between them and dissimilar to th...
The paper deals with a special class of cluster analysis methods where a membership degree is calcul...
This paper deals with a new method of fuzzy clustering. The basic concepts of the method are introdu...
A hard partition clustering algorithm assigns equally distant points to one of the clusters, where e...
Abstract. In this paper, we study and improve the fuzzy clustering index and clustering algorithm pr...
The fuzzy clustering algorithm is to classify the data or indicators with a greater degree of simila...
This chapter provides a comprehensive, focused introduction to clustering, viewed as a fundamental m...
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