Investigation of a Novel Knowledge Operation Model Based on Rough Set Theory
Rongzhen Zhao, Cuiming Li, Chao Li · 2009
To advance the machinery performances, obviously the intelligent decision-making technologies will bring into play the significant power. Aimed at knowledge acquisition bottleneck, in the paper to take rough set theory (RST) as a knowledge discovery tool and resolve the puzzle was explored. Both the tool's principle and its application way in machinery engineering were investigated. A novel knowledge operation model is brought forward. It shows that the knowledge discovery based on RST is a system engineering project. But to obtain the original knowledge resource should be the essential foundation. The special request for RST tool is that the data must also be concise. So, to protect the expected knowledge with scientific data mode has become the significant task in knowledge discovery researches at present. But the case of simulative faults experiments on a rotating machinery model indicates that the task can be accomplished by arduous efforts.