scholarly journals Ensemble Based Gustafson Kessel Fuzzy Clustering

2018 ◽  
Vol 1 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Achmad Fauzi Bagus Firmansyah ◽  
Setia Pramana
Keyword(s):  
Fuzzy Clustering ◽  
Covariance Estimation ◽  
Correlated Data ◽  
Fuzzy Membership ◽  
Clustering Method ◽  
Cluster Ensemble ◽  
Cluster Membership ◽  
Random Initialization ◽  
Hard Clustering ◽  
Membership Matrix

Fuzzy clustering is a clustering method whcih allows an object to belong to two or more cluster by combining hard-clustering and fuzzy membership matrix. Two popular algorithms used in fuzzy clustering are Fuzzy C-Means (FCM) and Gustafson Kessel (GK). The FCM use Euclideans distance for determining cluster membership, while GK use Fuzzy Covariance Matrix that considering covariance between variables. Although GK perform better, it has some drawbacks on handling linearly correlated data, and as FCM the algorithm produce unstable result due to random initialization. These drawbacks can be overcame by using improved covariance estimation and cluster ensemble, respectively. This research presents the implementation of improved covariance estimation and cluster ensemble on GK method and compare it with FCM-Ensemble.

GT2-CFC: General Type-2 Collaborative Fuzzy Clustering method

2021 ◽  
Author(s):  
Fariba Salehi ◽  
Mohammad Reza Keyvanpour ◽  
Arash Sharifi
Keyword(s):  
Fuzzy Clustering ◽  
General Type ◽  
Clustering Method ◽  
Fuzzy Clustering Method

scholarly journals FUZZY CLUSTERING MEANS (FCM) DALAM PENENTUAN LOKASI PENERTIBAN PENYAKIT MASYARAKAT PADA KEGIATAN PEMBINAAN SOSIAL SATPOL-PP WILAYAH SUMATRA-BARAT

Petir ◽  
2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Redaksi Tim Jurnal
Keyword(s):  
Fuzzy Clustering ◽  
Community Policing ◽  
Sex Workers ◽  
Data Clustering ◽  
Behavior Patterns ◽  
Clustering Method ◽  
Street Vendors ◽  
West Sumatra ◽  
Municipal Police ◽  
Disease Community

Based on the data summary disease community policing activities by municipal police pp city of West Sumatra in January 2010 to December 2014, there were as many as 1660 cases of approximately 20 locations enforcement. Each location policing there are various types of activities are classified as a disease of society. Based on data obtained are activities that have curbed such as street vendors, illegal buildings, street children, street, commercial sex workers (CSWs) and others. Number of activities at each point different locations each year, thus requiring data clustering method to facilitate the investigation team in determining the behavior patterns of disease activity as a description of the location community policing a priority next year. The method used in this data clustering method is to use Fuzzy Clustering Means (FCM)

Using Fuzzy Clustering Method to Classify the Component in the Process of Software Evolution

2012 ◽  
Vol 11 (3) ◽  
pp. 396-398 ◽  
Author(s):  
Jian Wang ◽  
Na Zhao ◽  
Wei Du ◽  
Yang Zhao ◽  
Ye Qian ◽  
...  
Keyword(s):  
Fuzzy Clustering ◽  
Software Evolution ◽  
Clustering Method ◽  
Fuzzy Clustering Method

A New Clustering Method with Fuzzy Approach Based on Takagi-Sugeno Model in Queuing Systems

2013 ◽  
Vol 3 (2) ◽  
pp. 32-54
Author(s):  
Farzaneh Gholami Zanjanbar ◽  
Inci Sentarli
Keyword(s):  
Fuzzy Model ◽  
Extraction Process ◽  
Queuing System ◽  
Rule Base ◽  
Queuing Systems ◽  
Clustering Method ◽  
Hard Clustering ◽  
Sugeno Model ◽  
Takagi Sugeno ◽  
Linear Controllers

In this paper, the authors propose a new hard clustering method to provide objective knowledge on field of fuzzy queuing system. In this method, locally linear controllers are extracted and translated into the first-order Takagi-Sugeno rule base fuzzy model. In this extraction process, the region of fuzzy subspaces of available inputs corresponding to different implications is used to obtain the clusters of outputs of the queuing system. Then, the multiple regression functions associated with these separate clusters are used to interpret the performance of queuing systems. An application of the method also is presented and the performance of the queuing system is discussed.

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