TY - JOUR
T1 - DNA approach to solve clustering problem based on a mutual order
AU - Bakar, Rohani Binti Abu
AU - Watada, Junzo
AU - Pedrycz, Witold
PY - 2008/1
Y1 - 2008/1
N2 - Clustering is regarded as a consortium of concepts and algorithms that are aimed at revealing a structure in highly dimensional data and arriving at a collection of meaningful relationships in data and information granules. The objective of this paper is to propose a DNA computing to support the development of clustering techniques. This approach is of particular interest when dealing with huge data sets, unknown number of clusters and encountering a heterogeneous character of available data. We present a detailed algorithm and show how the essential components of the clustering technique are realized through the corresponding mechanisms of DNA computing. Numerical examples offer a detailed insight into the performance of the DNA-based clustering.
AB - Clustering is regarded as a consortium of concepts and algorithms that are aimed at revealing a structure in highly dimensional data and arriving at a collection of meaningful relationships in data and information granules. The objective of this paper is to propose a DNA computing to support the development of clustering techniques. This approach is of particular interest when dealing with huge data sets, unknown number of clusters and encountering a heterogeneous character of available data. We present a detailed algorithm and show how the essential components of the clustering technique are realized through the corresponding mechanisms of DNA computing. Numerical examples offer a detailed insight into the performance of the DNA-based clustering.
KW - Cluster validity
KW - Clustering
KW - DNA computing and optimization
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U2 - 10.1016/j.biosystems.2007.06.002
DO - 10.1016/j.biosystems.2007.06.002
M3 - Article
C2 - 17669585
AN - SCOPUS:37349037847
SN - 0303-2647
VL - 91
SP - 1
EP - 12
JO - Currents in modern biology
JF - Currents in modern biology
IS - 1
ER -