With respect to the cluster problem of the evaluation information of mass customers in service management, a cluster algorithm of new Gaussian kernel FCM (fuzzy C-means) is proposed based on the idea of FCM. First, the paper defines a Euclidean distance formula between two data points and makes them cluster adaptively based on the distance classification approach and nearest neighbors in deleting relative data. Second, the defects of the FCM algorithm are analyzed, and a solution algorithm is designed based on the dual goals of obtaining a short distance between whole classes and long distances between different classes. Finally, an example is given to illustrate the results compared with the existing FCM algorithm
Fuzzy C-means (FCM) is a powerful clustering algorithm and has been introduced to overcome the crisp...
Fuzzy clustering algorithms are widely used in many fields, more and more research results have been...
Aiming at partitioning an image into homogeneous and meaningful regions, automatic image segmentatio...
The fuzzy clustering algorithm has been widely used in the research area and production and life. Ho...
Clustering algorithms are an integral part of both computational intelligence and pattern recognitio...
Abstract:-Fuzzy C-Means (FCM) clustering algorithm is used in a variety of application domains. Fund...
[[abstract]]The popular fuzzy c-means algorithm (FCM) is an objective function based clustering meth...
Abstract—Some of the well-known fuzzy clustering algorithms are based on Euclidean distance function...
[[abstract]]Some of the well-known fuzzy clustering algorithms are based on Euclidean distance funct...
In GK-algorithm, modified Mahalanobis distance with preserved volume was used. However, the added fu...
The fuzziness index m has important influence on the clustering result of fuzzy clustering algorithm...
Fuzzy C-Means (FCM) is a data clustering technique where the existence of each data point in a clust...
Fuzzy C-means (FCM) is an important clustering algorithm with broad applications such as retail mark...
Virtually every sector of business and industry that use computing, including financial analysis, se...
Kernel approaches call improve the performance of conventional Clustering or classification algorith...
Fuzzy C-means (FCM) is a powerful clustering algorithm and has been introduced to overcome the crisp...
Fuzzy clustering algorithms are widely used in many fields, more and more research results have been...
Aiming at partitioning an image into homogeneous and meaningful regions, automatic image segmentatio...
The fuzzy clustering algorithm has been widely used in the research area and production and life. Ho...
Clustering algorithms are an integral part of both computational intelligence and pattern recognitio...
Abstract:-Fuzzy C-Means (FCM) clustering algorithm is used in a variety of application domains. Fund...
[[abstract]]The popular fuzzy c-means algorithm (FCM) is an objective function based clustering meth...
Abstract—Some of the well-known fuzzy clustering algorithms are based on Euclidean distance function...
[[abstract]]Some of the well-known fuzzy clustering algorithms are based on Euclidean distance funct...
In GK-algorithm, modified Mahalanobis distance with preserved volume was used. However, the added fu...
The fuzziness index m has important influence on the clustering result of fuzzy clustering algorithm...
Fuzzy C-Means (FCM) is a data clustering technique where the existence of each data point in a clust...
Fuzzy C-means (FCM) is an important clustering algorithm with broad applications such as retail mark...
Virtually every sector of business and industry that use computing, including financial analysis, se...
Kernel approaches call improve the performance of conventional Clustering or classification algorith...
Fuzzy C-means (FCM) is a powerful clustering algorithm and has been introduced to overcome the crisp...
Fuzzy clustering algorithms are widely used in many fields, more and more research results have been...
Aiming at partitioning an image into homogeneous and meaningful regions, automatic image segmentatio...