NDLI: Hybrid Kohonen Self Organizing Map for the Uncertainty Involved in Overlapping Clusters Using Simulated Annealing

Content Provider	IEEE Xplore Digital Library
Author	Mohebi, E. Sap, M.N.M.
Copyright Year	2009
Abstract	The Kohonen self organizing map is widely used as a popular tool in the exploratory phase of data mining. The SOM (Self Organizing Maps) maps high dimensional space into a 2-dimensional grid by placing similar elements close together, forming clusters. Recently research experiments presented that to capture the uncertainty involved in cluster analysis, it is not necessary to have crisp boundaries in some clustering operations. In this paper to overcome the uncertainty, an optimized clustering algorithm based on SOM which employs the rough set theory and the Simulated Annealing as a general technique for optimization problems is proposed. The optimized two-level stage SA-Rough SOM (Simulated Annealing – Rough Self Organizing Map) (first using SOM to produce the prototypes that are then clustered in the second stage based on the combination of rough set and simulated annealing) is found to perform well and more accurate compared with the crisp clustering methods (i.e. Incremental SOM) and reduces the errors.
Starting Page	53
Ending Page	58
File Size	270856
Page Count	6
File Format	PDF
ISBN	9781424437719
DOI	10.1109/UKSIM.2009.28
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-03-25
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Uncertainty Computational modeling Computer simulation Neurons Self Organizing Map uncertainty Organizing Rough set Space technology Signal processing algorithms Clustering algorithms Simulated annealing Set theory clustering Simulated Annealing.
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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