Add to ORKGThis paper presents a fuzzy c-means clustering method for partitioning symbolic interval data, namely the T-S fuzzy rules. The proposed method furnish a fuzzy partition and prototype for each cluster by optimizing an adequacy criterion based on suitable squared Euclidean distances between vectors of intervals. This methodology leads to a fuzzy partition of the TS-fuzzy rules, one for each cluster, which corresponds to a new set of fuzzy sub-systems. When applied to the clustering of TS-fuzzy system the result is a set of additive decomposed TS-fuzzy sub-systems. In this work a generalized Probabilistic Fuzzy C-Means algorithm is proposed and applied to TS-Fuzzy System clustering
This paper presents a possibilistic fuzzy clustering algorithm that is applied to a multidimensional...
Abstract: Fuzzy rules have a simple structure within a multidimensional vector space and they are pr...
Clustering refers to the process of unsupervised partitioning of a data set based on a dissimilarity...
The fuzzy c-means (FCM) clustering algorithm is the best known and used method in fuzzy clustering ...
This paper presents the development, testing and evaluation of generalized Possibilistic fuzzy c-m...
The Fuzzy C-Means (FCM) clustering algorithm is the best known and the most used method for fuzzy cl...
The Fuzzy C-Means (FCM) clustering algorithm is the best known and the most used method for fuzzy cl...
A fuzzy system entirely characterizes one region of the input-output product space S=U×Vthrough a ...
This paper presents a fuzzy c-means clustering method for decompose a T-S fuzzy system. This techniq...
A fuzzy system entirely characterizes one region of the input-output product space S=U×Vthrough a ...
Abstract- A fuzzy system entirely characterizes one region of the input-output product space S U V =...
AbstractWhile many clustering techniques for interval-valued data have been proposed, there has been...
A design methodology of interval type-2 fuzzy c-means clustering algorithm-based fuzzy inference sys...
Abstract: This paper introduces a new method for fuzzy modeling based on set of input-output data pa...
Abstract — Clustering is a collection of objects which are similar between them and dissimilar to th...
This paper presents a possibilistic fuzzy clustering algorithm that is applied to a multidimensional...
Abstract: Fuzzy rules have a simple structure within a multidimensional vector space and they are pr...
Clustering refers to the process of unsupervised partitioning of a data set based on a dissimilarity...
The fuzzy c-means (FCM) clustering algorithm is the best known and used method in fuzzy clustering ...
This paper presents the development, testing and evaluation of generalized Possibilistic fuzzy c-m...
The Fuzzy C-Means (FCM) clustering algorithm is the best known and the most used method for fuzzy cl...
The Fuzzy C-Means (FCM) clustering algorithm is the best known and the most used method for fuzzy cl...
A fuzzy system entirely characterizes one region of the input-output product space S=U×Vthrough a ...
This paper presents a fuzzy c-means clustering method for decompose a T-S fuzzy system. This techniq...
A fuzzy system entirely characterizes one region of the input-output product space S=U×Vthrough a ...
Abstract- A fuzzy system entirely characterizes one region of the input-output product space S U V =...
AbstractWhile many clustering techniques for interval-valued data have been proposed, there has been...
A design methodology of interval type-2 fuzzy c-means clustering algorithm-based fuzzy inference sys...
Abstract: This paper introduces a new method for fuzzy modeling based on set of input-output data pa...
Abstract — Clustering is a collection of objects which are similar between them and dissimilar to th...
This paper presents a possibilistic fuzzy clustering algorithm that is applied to a multidimensional...
Abstract: Fuzzy rules have a simple structure within a multidimensional vector space and they are pr...
Clustering refers to the process of unsupervised partitioning of a data set based on a dissimilarity...