نتایج جستجو برای: fuzzified fcm

تعداد نتایج: 3422  

2012
S. RAJKUMAR V. NARAYANI P. VICTOR

Nowadays in this competitive world of job seekers, the necessity of job makes many recruiters to provide more cautious on their selection process. The recruitment process is definitely a fuzzified anomaly for all the components available in the environment. The art of deception also changes its face with a modern artistic fashion. This paper deals with the uncertainty features which play the ma...

2012
B. Fergani Mohamed-khireddine Kholladi M. Bahri

In fuzzy clustering, the fuzzy c-means (FCM) clustering algorithm is the best known and used method. An interesting extension of FCM is the fuzzy ISODATA (FISODATA) algorithm; it updates cluster number during the algorithm. That's why we can have more or less clusters than the initialization step. It's the power of the fuzzy ISODATA algorithm comparing to FCM. The aim of this paper is...

Journal: :PROCEEDINGS OF HYDRAULIC ENGINEERING 1994

2015
Tatiana Afanasieva Nadezhda Yarushkina Mkrtich Toneryan Denis Zavarzin Alexei Sapunkov Ivan Sibirev

The aim of this contribution is to show the opportunities of applying of fuzzy time series models to predict multiple heterogeneous time series, given at International Time Series Forecasting Competition [http://irafm.osu.cz/cif/main.php]. The dataset of this competition includes 91 time series of different length, time frequencies and behaviour. In this paper the framework (algorithm) of multi...

Journal: :PROCEEDINGS OF HYDRAULIC ENGINEERING 1997

Journal: :IJSIR 2011
Hongwei Mo Yujing Yin

This paper addresses the issue of image segmentation by clustering in the domain of image processing. The clustering algorithm taken account here is the Fuzzy C-Means which is widely adopted in this field. Bacterial Foraging Optimization Algorithm is an optimal algorithm inspired by the foraging behavior of E.coli. For the purpose to reinforce the global search capability of FCM, the Bacterial ...

2014
Horng-Lin Shieh

A robust validity index for fuzzy c-means (FCM) algorithm is proposed in this paper. The purpose of fuzzy clustering is to partition a given set of training data into several different clusters that can then be modeled by fuzzy theory. The FCM algorithm has become the most widely used method in fuzzy clustering. Although, there are some successful applications of FCM have been proposed, a disad...

Journal: :Cytometry. Part A : the journal of the International Society for Analytical Cytology 2009
Carole Elbim Gérard Lizard

Flow cytometric analysis provides a rapid screen for abnormalities of polymorphonuclear neutrophils (PMN) function and reflect their behavior in vivo more accurately. This review summarizes the major fluorescent probes used to study PMN oxidative burst and apoptosis using flow cytometry (FCM). We also provide examples of FCM studies in physiological and pathological situations, illustrating the...

2014
Yinghua Lu Tinghuai Ma Changhong Yin Xiaoyu Xie Wei Tian ShuiMing Zhong

An improved fuzzy c-means algorithm is put forward and applied to deal with meteorological data on top of the traditional fuzzy c-means algorithm. The proposed algorithm improves the classical fuzzy c-means algorithm (FCM) by adopting a novel strategy for selecting the initial cluster centers, to solve the problem that the traditional fuzzy c-means (FCM) clustering algorithm has difficulty in s...

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