NDLI: An improved fuzzy C-means clustering algorithm based on simulated annealing

Content Provider	IEEE Xplore Digital Library
Author	Peiyu Liu Linshan Duan Xuezhi Chi Zhenfang Zhu
Copyright Year	2013
Description	Author affiliation: Shandong Police Coll., Jinan, China (Xuezhi Chi) \|\| Sch. of Inf. Sci. & Electr. Eng., Shandong Jiao tong Univ., Jinan, China (Zhenfang Zhu) \|\| Dept. of Inf. Sci. & Eng., Shandong Normal Univ., Jinan, China (Peiyu Liu; Linshan Duan)
Abstract	Fuzzy C-means clustering algorithm (FCM) is a widely used clustering algorithm, however it has its drawbacks: the initial number of clusters needs to be determined by the manual control according to the prior knowledge; the objective function ignores the disequilibrium problems among the sample attribute data. In view of these problems, this paper proposes a sample weighted FCM algorithm based on simulated annealing algorithm. It uses the simulated annealing algorithm which has an excellent ability of seeking global optimal solution to calculate the initial value of the number of clusters and makes certain weighting process on the clustering center function and the objective function. The experiment results show that this proposed algorithm has better classification accuracy and classification accuracy rate compared with FCM algorithm and the common sample weighted FCM clustering algorithms. Meanwhile, this algorithm needs not to be determined the initial value of clusters manually. The improved algorithm possesses the superiority and the actual application value.
Sponsorship	IEEE Circuits Syst. Soc.
Starting Page	39
Ending Page	43
File Size	243199
Page Count	5
File Format	PDF
ISBN	9781467352536
DOI	10.1109/FSKD.2013.6816163
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Fuzzy C-means clustering algorithm Accuracy Simulated Annealing Clustering algorithms Simulated annealing Linear programming Educational institutions sample weighting Classification algorithms
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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