نتایج جستجو برای: parallel fuzzy c means clustering

تعداد نتایج: 1718346  

2014
Tejwant Singh Manish Mahajan

Fuzzy C-Mean (FCM) is an unsupervised clustering algorithm based on fuzzy set theory that allows an element to belong to more than one cluster. Where fuzzy means “unclear” or “not defined” and c denotes “clustering”. In FCM the number of cluster are randomly selected. [15] FCM is the advanced version of K-means clustering algorithm and doing more work than K-means. K-Means just needs to do a di...

2014
Jingfeng Yan

Middle spatial resolution multi-spectral remote sensing image is a kind of color image with low contrast, fuzzy boundaries and informative features. In view of these features, the fuzzy C-means clustering algorithm is an ideal choice for image segmentation. However, fuzzy C-means clustering algorithm requires a pre-specified number of clusters and costs large computation time, which is easy to ...

2014
Bryant Aaron Dan E. Tamir Naphtali D. Rishe Abraham Kandel

Researchers have observed that multistage clustering can accelerate convergence and improve clustering quality. Two-stage and two-phase fuzzy C-means (FCM) algorithms have been reported. In this paper, we demonstrate that the FCM clustering algorithm can be improved by the use of static and dynamic single-pass incremental FCM procedures. Keywords-Clustering; Fuzzy C-Means Clustering; Incrementa...

2014
Jiulun Fan Jing Li J. L. Fan J. Li

Suppressed fuzzy c-means (S-FCM) clustering algorithm with the intention of combining the higher speed of hard c-means clustering algorithm and the better classification performance of fuzzy c-means clustering algorithm had been studied by many researchers and applied in many fields. In the algorithm, how to select the suppressed rate is a key step. In this paper, we give a method to select the...

2012
A. H. Hadjahmadi M. M. Homayounpour S. M. Ahadi

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some kinds...

Journal: :Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 2006

Journal: :Acta Universitatis Sapientiae, Informatica 2020

Journal: :International Journal of Computer Applications 2012

2004
Watcharachai Wiriyasuttiwong

This paper presents an application of fuzzy c-means clustering to designing the fuzzy logic controller for the temperature control in electric ceramics kiln. This research aims to controlling the temperature in firing step of burning the ceramic products which were coated with black, intensely red and green chemical substances. The experimental results show that the fuzzy c-means clustering des...

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