نتایج جستجو برای: fuzzy c means algorithm

تعداد نتایج: 2110543  

Journal: :ICST Transactions on Scalable Information Systems 2023

Possibilistic fuzzy c-means (PFCM) is one of the most widely used clustering algorithm that solves noise sensitivity problem Fuzzy (FCM) and coincident clusters possibilistic (PCM). Though PFCM a highly reliable but efficiency can be further improved by introducing concept suppression. Suppression-based algorithms employ winner non-winner based suppression technique on datasets, helping in perf...

Journal: :journal of advances in computer research 0
masoumeh pourhasan department of computer engineering, faculty of engineering, chalous branch, islamic azad university, chalous, mazandaran, iran abbas karimi department of computer engineering, faculty of engineering, arak branch, islamic azad university, arak, markazi, iran

some applications are critical and must designed fault tolerant system. usually voting algorithm is one of the principle elements of a fault tolerant system. two kinds of voting algorithm are used in most applications, they are majority voting algorithm and weighted average algorithm these algorithms have some problems. majority confronts with the problem of threshold limits and voter of weight...

2012
Neha Jain Seema Shukla

In recent years, the Fuzzy Relational Database and its queries have gradually become a new research topic. Fuzzy Structured Query Language (FSQL) is used to retrieve the data from fuzzy database because traditional Structured Query Language (SQL) is inefficient to handling uncertain and vague queries. The proposed model provides the facility for naïve users for retrieving relevant results of no...

2014
Chen-Chia Chuang Jin-Tsong Jeng Sheng-Chieh Chang

Clustering algorithms have been widely used artificial intelligence, data mining and machine learning, etc. It is unsupervised classification and is divided into groups according to data sets. That is, the data sets of similarity partition belong to the same group; otherwise data sets divide other groups in the clustering algorithms. In general, to analysis interval data needs Type II fuzzy log...

Journal: :Pattern Recognition 1991
Mohamed S. Kamel Shokri Z. Selim

In this paper, the problem of achieving 'semi-fuzzy' or 'soft' clustering of multidimensional data is discussed.A technique based on thresholding the results of the fuzzy c-means algorithm is introduced.The proposed approach is analysed and contrasted with the soft clustering method (see S. Z. Selim and M. A. Ismail, Pattern Recognition 17, 559-568) showing the merits of the new method.Separati...

2012
Yang Yu Bingbing Zhang Bing Rao Liang Chen

Abstract The priori knowledge of the radar can not be used by the traditional fuzzy C-means clustering algorithm, which leads a poor accuracy of the data association. An improved fuzzy C-means clustering algorithm is proposed in this paper. The real-time change rate of the track slope of moving targets measured by radar is used to update the weight. Then the objective function of fuzzy C-means ...

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...

Journal: :International Journal on Advanced Science, Engineering and Information Technology 2019

2011
Kiran Jyoti Satyaveer Singh

In this paper proposes different conventional and fuzzy based clustering techniques for fault detection and isolation in process plant monitoring. Process plant monitoring is very important aspect to improve productiveness and efficiency of the product and plant. This paper takes a case study of plant data and implements K means algorithm and fuzzy C means algorithm to cluster the relevant data...

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