DNA approach to solve clustering problem based on a mutual order.
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.
Bakar
Rohani Binti Abu
RB
Graduate School of Information, Production and Systems, Waseda University, 2-7 Hibikino, Wakamatsu-Ku, Kitakyushu-Shi 808-0135, Japan. rohani@ump.edu.my
Watada
Junzo
J
Pedrycz
Witold
W
D000465:Algorithms; D001483:Base Sequence; D019295:Computational Biology; D004247:DNA / Q000737:chemistry / Q000235:genetics*; D008969:Molecular Sequence Data; D005810:Multigene Family / Q000235:genetics*; D009690:Nucleic Acid Conformation
D004247:DNA