A DNA-based clustering method based on statistics adapted to heterogeneous coordinate data

Ikno Kim, Junzo Watada

    研究成果: Conference contribution

    3 被引用数 (Scopus)

    抄録

    A cluster analysis is often used in social sciences, management, general science and engineering, etc. with the objective of characterising structures in heterogeneous data sets. In this case, collections of information granules are obviously constructed through clustering techniques. However, clustering problems are intractable and NP-complete problems with a number of patterns. In this article, we discuss the use of DNA computing as a vehicle of heterogeneous coordinated data clustering, and elaborate on the fundamentals of DNA computing in the context of clustering tasks. A novel DNA-based clustering method is proposed, using statistics-based encoding of DNA strands, for clustering coordinated data from simulated DNA studies and experiments. The results also show the capabilities of this method when adapted to heterogeneous coordinate data.

    本文言語English
    ホスト出版物のタイトルProceedings of the International Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009
    ページ892-897
    ページ数6
    DOI
    出版ステータスPublished - 2009
    イベントInternational Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009 - Fukuoka
    継続期間: 2009 3 162009 3 19

    Other

    OtherInternational Conference on Complex, Intelligent and Software Intensive Systems, CISIS 2009
    CityFukuoka
    Period09/3/1609/3/19

    ASJC Scopus subject areas

    • Hardware and Architecture
    • Software
    • Control and Systems Engineering

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