A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis

Xiang Wang; Rui Guo; Jizhong Liu; Xiaoying Gao; Lina Wang; Wei Lei; Zhiying Liu; Chi Zhang; Ke Zuo

doi:10.1109/PACIIA.2008.286

A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis

Xiang Wang
, Rui Guo^*
, Jizhong Liu
, Xiaoying Gao
, Lina Wang
, Wei Lei
, Zhiying Liu
, Chi Zhang
, Ke Zuo

^*Corresponding author for this work

School of Electronic and Information Engineering

Beihang University
Beijing Simulation Center

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Proposed a novel Fuzzy Cluster Algorithm-AWFCM, aiming at large miss-clustering and invalidation in the Fuzzy C-means Algorithm when has noises and uneven samples situation. This new algorithm defined a new distance in new metric space and introduced weight matrix based on sample dots' density. New definition of distance can efficiently restrain the error range of clustering centers for samples with noise points in iteration, meanwhile improve recursion for clustering centers according to samples' density. Experiments have proved that AWFCM algorithm overcomes bugs of FCM algorithm to a certain extent, with favorable convergence and robust.

Original language	English
Title of host publication	Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008
Pages	130-134
Number of pages	5
DOIs	https://doi.org/10.1109/PACIIA.2008.286
State	Published - 2008
Event	2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008 - Wuhan, China Duration: 19 Dec 2008 → 20 Dec 2008

Publication series

Name	Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008
Volume	2

Conference

Conference	2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008
Country/Territory	China
City	Wuhan
Period	19/12/08 → 20/12/08

Keywords

AWFCM
Clustering
Distance
FCM
Weighted

Access to Document

10.1109/PACIIA.2008.286

Cite this

Wang, X., Guo, R., Liu, J., Gao, X., Wang, L., Lei, W., Liu, Z., Zhang, C., & Zuo, K. (2008). A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis. In Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008 (pp. 130-134). Article 4756750 (Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008; Vol. 2). https://doi.org/10.1109/PACIIA.2008.286

Wang, Xiang ; Guo, Rui ; Liu, Jizhong et al. / A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis. Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008. 2008. pp. 130-134 (Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008).

@inproceedings{2a8681366ed941b38f6ce857df3d3603,

title = "A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis",

abstract = "Proposed a novel Fuzzy Cluster Algorithm-AWFCM, aiming at large miss-clustering and invalidation in the Fuzzy C-means Algorithm when has noises and uneven samples situation. This new algorithm defined a new distance in new metric space and introduced weight matrix based on sample dots' density. New definition of distance can efficiently restrain the error range of clustering centers for samples with noise points in iteration, meanwhile improve recursion for clustering centers according to samples' density. Experiments have proved that AWFCM algorithm overcomes bugs of FCM algorithm to a certain extent, with favorable convergence and robust.",

keywords = "AWFCM, Clustering, Distance, FCM, Weighted",

author = "Xiang Wang and Rui Guo and Jizhong Liu and Xiaoying Gao and Lina Wang and Wei Lei and Zhiying Liu and Chi Zhang and Ke Zuo",

year = "2008",

doi = "10.1109/PACIIA.2008.286",

language = "英语",

isbn = "9780769534909",

series = "Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008",

pages = "130--134",

booktitle = "Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008",

note = "2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008 ; Conference date: 19-12-2008 Through 20-12-2008",

}

Wang, X, Guo, R, Liu, J, Gao, X, Wang, L, Lei, W, Liu, Z, Zhang, C & Zuo, K 2008, A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis. in Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008., 4756750, Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008, vol. 2, pp. 130-134, 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008, Wuhan, China, 19/12/08. https://doi.org/10.1109/PACIIA.2008.286

A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis. / Wang, Xiang; Guo, Rui; Liu, Jizhong et al.
Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008. 2008. p. 130-134 4756750 (Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis

AU - Wang, Xiang

AU - Guo, Rui

AU - Liu, Jizhong

AU - Gao, Xiaoying

AU - Wang, Lina

AU - Lei, Wei

AU - Liu, Zhiying

AU - Zhang, Chi

AU - Zuo, Ke

PY - 2008

Y1 - 2008

N2 - Proposed a novel Fuzzy Cluster Algorithm-AWFCM, aiming at large miss-clustering and invalidation in the Fuzzy C-means Algorithm when has noises and uneven samples situation. This new algorithm defined a new distance in new metric space and introduced weight matrix based on sample dots' density. New definition of distance can efficiently restrain the error range of clustering centers for samples with noise points in iteration, meanwhile improve recursion for clustering centers according to samples' density. Experiments have proved that AWFCM algorithm overcomes bugs of FCM algorithm to a certain extent, with favorable convergence and robust.

AB - Proposed a novel Fuzzy Cluster Algorithm-AWFCM, aiming at large miss-clustering and invalidation in the Fuzzy C-means Algorithm when has noises and uneven samples situation. This new algorithm defined a new distance in new metric space and introduced weight matrix based on sample dots' density. New definition of distance can efficiently restrain the error range of clustering centers for samples with noise points in iteration, meanwhile improve recursion for clustering centers according to samples' density. Experiments have proved that AWFCM algorithm overcomes bugs of FCM algorithm to a certain extent, with favorable convergence and robust.

KW - AWFCM

KW - Clustering

KW - Distance

KW - FCM

KW - Weighted

UR - https://www.scopus.com/pages/publications/63149114721

U2 - 10.1109/PACIIA.2008.286

DO - 10.1109/PACIIA.2008.286

M3 - 会议稿件

AN - SCOPUS:63149114721

SN - 9780769534909

T3 - Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008

SP - 130

EP - 134

BT - Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008

T2 - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008

Y2 - 19 December 2008 through 20 December 2008

ER -

Wang X, Guo R, Liu J, Gao X, Wang L, Lei W et al. A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis. In Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008. 2008. p. 130-134. 4756750. (Proceedings - 2008 Pacific-Asia Workshop on Computational Intelligence and Industrial Application, PACIIA 2008). doi: 10.1109/PACIIA.2008.286

A novel alternative weighted fuzzy c-means algorithm and cluster validity analysis

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