Spatial Cluster Analysis by the Adleman-Lipton DNA Computing Model and Flexible Grids

Spatial cluster analysis is an important data-mining task. Typical techniques include CLARANS, density- and gravity-based clustering, and other algorithms based on traditional von Neumann’s computing architecture. The purpose of this paper is to propose a technique for spatial cluster analysis based...

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Bibliographic Details
Published inDiscrete Dynamics in Nature and Society Vol. 2012; no. 1; pp. 197 - 228-215
Main Authors Liu, Xiyu, Xiang, Laisheng, Wang, Xin
Format Journal Article
LanguageEnglish
Published New York Hindawi Limiteds 01.01.2012
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Wiley
Subjects
Algorithms
Cluster analysis
Deoxyribonucleic acid
DNA
Studies
Online AccessGet full text
ISSN1026-0226
1607-887X
1607-887X
DOI10.1155/2012/894207

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Summary:Spatial cluster analysis is an important data-mining task. Typical techniques include CLARANS, density- and gravity-based clustering, and other algorithms based on traditional von Neumann’s computing architecture. The purpose of this paper is to propose a technique for spatial cluster analysis based on DNA computing and a grid technique. We will adopt the Adleman-Lipton model and then design a flexible grid algorithm. Examples are given to show the effect of the algorithm. The new clustering technique provides an alternative for traditional cluster analysis.
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ISSN:1026-0226
1607-887X
1607-887X
DOI:10.1155/2012/894207