Knowledge Acquisition Method Based on Rough Set for Fault Diagnosis for Imperial Pb-Zn Smelting Furnace
Xiaoying Liu · Journal of Chinese Computer Systems · 2006
A knowledge acquisition method for incomplete data sets knowledge acquisition is proposed for fault diagnosis of Imperial Pb-Zn Smelting Furnace (ISF) knowledge base based on the concept of equivalence classes of rough set theory. Two kinds of partitions are formed in the training examples of incomplete data sets:lower approximations and upper approximations.Unknown characteristics are supposed at random,then lower approximations and upper approximations can be computed.At last,certain rules and uncertain rules with rules probability can be deduced,and appropriate estimate of unknown characteristics can also be obtained.The knowledge acquisition example of ISP shows its validity and practicability.