نتایج جستجو برای: fuzzy c means clustering algorithms

تعداد نتایج: 1808735  

Journal: :journal of mining and environment 0
h. fattahi department of mining engineering, arak university of technology, arak, iran

slope stability analysis is an enduring research topic in the engineering and academic sectors. accurate prediction of the factor of safety (fos) of slopes, their stability, and their performance is not an easy task. in this work, the adaptive neuro-fuzzy inference system (anfis) was utilized to build an estimation model for the prediction of fos. three anfis models were implemented including g...

Journal: :Appl. Soft Comput. 2011
Erdal Kayacan Yesim Oniz Ayse Cisel Aras Okyay Kaynak Rahib Hidayat Abiyev

A type-2 Takagi-Sugeno-Kang fuzzy neural system is proposed and its parameter update rules are derived using fuzzy clustering and gradient learning algorithms. The proposed type-2 fuzzy neural system is used for the control and the identification of a real-time servo system. Fuzzy c-means clustering algorithm is used to determine the initial places of the membership functions to ensure that the...

Journal: :European Journal of Operational Research 2006
Sueli A. Mingoti Joab O. Lima

In this paper we present a comparison among some nonhierarchical and hierarchical clustering algorithms including SOM (Self-Organization Map) neural network and Fuzzy c-means methods. Data were simulated considering correlated and uncorrelated variables, nonoverlapping and overlapping clusters with and without outliers. A total of 2530 data sets were simulated. The results showed that Fuzzy c-m...

2011
J. Hossen

The clustering algorithm hybridization scheme has become of research interest in data partitioning applications in recent years. The present paper proposes a Hybrid Fuzzy clustering algorithm (combination of Fuzzy C-means with extension and Subtractive clustering algorithm) for data classifications applications. The fuzzy c-means (FCM) and subtractive clustering (SC) algorithm has been widely d...

2016
Seok-Beom Roh Sung-Kwun Oh

The techniques to recycle and reuse plastics attract public attention. These public attraction and needs result in improving the recycling technique. However, the identification technique for black plastic wastes still have big problem that the spectrum extracted from near infrared radiation spectroscopy is not clear and is contaminated by noise. To overcome this problem, we apply Raman spectro...

2017
B. Venkataramana Srinivasa Rao

Data clustering has been considered as the most important raw data analysis method used in data mining technology. To extract the unknown valuable information from the large volume of data for so many real time applications are used in data classification. Most of the clustering techniques proved their efficiency in many applications such as decision making systems, medical sciences, earth scie...

2012
Shahin Ara Begum O. Mema Devi

As medical images contain uncertainties, there are difficulties in classification of images into homogeneous regions. Fuzzy sets, rough sets and the combination of fuzzy and rough sets plays a prominent role in formalizing uncertainty, vagueness, and incompleteness in diagnosis. Development of hybrid approaches for the segmentation of the magnetic resonance imaging (MRI) with the ability of com...

Journal: :International Journal of Advanced Computer Science and Applications 2013

2004
B. Moshiri

In this paper, utilization of clustering algorithms for data fusion in decision level is proposed. The results of automatic isolated word recognition, which are derived from speech spectrograph and Linear Predictive Coding (LPC) analysis, are combined with each other by using fuzzy clustering algorithms, especially fuzzy k-means and fuzzy vector quantization. Experimental results show that the ...

Journal: :Pattern Recognition Letters 2009
Marie-Hélène Masson Thierry Denoeux

A new clustering algorithm for proximity data, called RECM (Relational evidential c-means) is presented. This algorithm generates a credal partition, a new clustering structure based on the theory of belief functions, which extends the existing concepts of hard, fuzzy and possibilistic partitions. Two algorithms, EVCLUS (Evidential Clustering) and ECM (Evidential c-Means) were previously availa...

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