Applied Statistics by Means of DNA-Based Clustering for Data Classification

• KIM Ikno

  Graduate School of Information, Production and Systems, Waseda University

• JENG Don Jyh-Fu

  Institute of International Management, National Cheng Kung University

• WATADA Junzo

  Graduate School of Information, Production and Systems, Waseda University

抄録

In a clustering analysis, the main problem is often referred to the uncertainty of the data, which could be possibly clustered, meaning the quality of the designed, improved, or analysed system that could be evaluated by this uncertainty of the clustered data. A reliable optimal solution from clustering data could be found by making the best use ofDNA computing. In this paper, a reliable optimal algorithm is proposed to cluster specific data for supporting a complicated data structure based on DNA computing with applied statistics. Its realization is very challenging while the underlying goal could be easily understood in a dimensional space. Given their nature, clustering problems become NP-complete problems. The use of DNA computing as a vehicle of data clustering with applied statistics is discussed and described in this study.

収録刊行物

• バイオメディカル・ファジィ・システム学会大会講演論文集

  バイオメディカル・ファジィ・システム学会大会講演論文集 21 (0), 138-141, 2008

  バイオメディカル・ファジィ・システム学会

キーワード

• DNA computing
• ordering method
• splicing operation
• standard error
• statistical method

詳細情報

• CRID: 1390001205227905664
• NII論文ID: 110008136475
• DOI: 10.24466/pacbfsa.21.0_138
• ISSN: 24242586
• ISSN: 13451510
• 本文言語コード: en
• データソース種別:
  • JaLC
  • CiNii Articles
• 抄録ライセンスフラグ: 使用不可