A DNA-based algorithm for minimizing decision rules: A rough sets approach

Ikno Kim, Yu Yi Chu, Junzo Watada, Jui Yu Wu, Witold Pedrycz

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


Rough sets are often exploited for data reduction and classification. While they are conceptually appealing, the techniques used with rough sets can be computationally demanding. To address this obstacle, the objective of this study is to investigate the use of DNA molecules and associated techniques as an optimization vehicle to support algorithms of rough sets. In particular, we develop a DNA-based algorithm to derive decision rules of minimal length. This new approach can be of value when dealing with a large number of objects and their attributes, in which case the complexity of rough-sets-based methods is NP-hard. The proposed algorithm shows how the essential components involved in the minimization of decision rules in data processing can be realized.

Original languageEnglish
Article number6048012
Pages (from-to)139-151
Number of pages13
JournalIEEE Transactions on Nanobioscience
Issue number3
Publication statusPublished - Sept 2011


  • DNA-based algorithm
  • Data processing
  • decision rules
  • knowledge support system
  • rough sets

ASJC Scopus subject areas

  • Bioengineering
  • Electrical and Electronic Engineering
  • Biotechnology
  • Biomedical Engineering
  • Medicine (miscellaneous)
  • Computer Science Applications
  • Pharmaceutical Science


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