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Modifying Mountain Clustering Algorithm and Using It to Enhance the Performance of Fuzzy C-Means Algorithm

تعديل خوارزمية العنقدة الـMountain و استخدامها لتحسين أداء خوارزمية الـMeans-C الضبابية

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 Publication date 2017
and research's language is العربية
 Created by Shamra Editor




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In this paper, we introduce a modification to fuzzy mountain data clustering algorithm. We were able to make this algorithm working automatically, through finding a way to divide the space, to determine the values of the input parameters, and the stop condition automatically, instead of getting them by the user.

References used
YANG. M, AND WU. K, 2005- A Modified Mountain Clustering Algorithm, Published online:24 June 2005, London, p 125–138
CHIU. S, 1994- Fuzzy Model Identification Based on Cluster Estimate, journal of Intelligent and Fuzzy System, California, vol. 2, p 267-278
BERNETI. S, 2011- Design of Fuzzy Subtractive Clustering Model using Particle Swarm Optimization for the Permeability Prediction of the Reservoir, Islamic Azad University, Sari, Iran, Volume 29– No.11, September
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In this paper, we introduce a modification to fuzzy mountain data clustering algorithm. We were able to make this algorithm working automatically, through finding a way to divide the space, to determine the values of the input parameters, and the stop condition automatically, instead of getting them by the user.
This paper introduces a new algorithm to solve some problems that data clustering algorithms such as K-Means suffer from. This new algorithm by itself is able to cluster data without the need of other clustering algorithms.
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