Applied research of data mining in failure diagnosis based on rough sets and genetic algorithms
Kewen Li · Jisuanji gongcheng yu sheji · 2009
The combined method of rough sets theory and genetic algorithms is applied to data mining. By making use of operating data of the essential equipment in enterprises, rough sets theory is adopted to cut down redundant attributes, and the treated data act as a sample training set. Then the classified model is built by optimized genetic algorithms. On the basis of the classified model, the intrinsic regularity how the machine runs can be found, and the unknown breakdown equipment may be classified quickly, which will provide a powerful backing for failure diagnosis and failure prediction.