.png){kind=icon}
Return
A DNA-Based Algorithm for Minimizing Decision Rules: A Rough Sets Approach
.png){kind=icon}
PRE
AI
DOI：10.1109/TNB.2011.2168535.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
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.
Keywords:
Data processing
decision rules
DNA-based algorithm
knowledge support system
rough sets
Journal
IF:
4.4
Papers:
1.4K
Citations:
2.5K
Organization
Cited Papers
.png){kind=icon}
ShareSaveShareSaveShareSaveShareSaveShareSaveShareSaveBacteriocins and their applications for the treatment of bacterial diseases in aquaculture: a review
OAAI
OAAIShareSaveShareSaveShareSave
View more