基于粒度熵的知识约简算法应用
Application of Knowledge Reduction Algorithm Based on Granularity Entropy
张霞1
作者信息
摘要
针对现有的基于信息熵理论的知识约简算法存在的不完备性问题，提出了一种基于粒度熵的知识约简算法，并将其应用到电力变压器的故障诊断中。结果表明该算法可以从各约简集中筛选出最小最优的故障决策表约简集，从而提高故障诊断的速度和可靠性。
Abstract
In view of the incompleteness problem which existed in knowledge reduction algorithm based on information entropy theory, a knowledge reduction algorithm based on granular entropy and use its application to fault diagnosis of power transformer is proposed. The results show that the algorithm can focus screened the minimum optimal fault Decision Table Reduction set from each reduction to improve the speed and reliability of fault diagnosis.
关键词
知识约简/粒度熵/故障诊断Key words
knowledge reduction/granularity entropy/fault diagnosis引用本文复制引用
出版年
2015
NETL
NSTL
维普
万方数据