Application study of fault diagnosis based on variable precision rough set
Cai Rui-ying · Jisuanji gongcheng yu sheji · 2009
The standard rough set theory cannot effectively process the noise data, but there is always noise data in fault diagnosis data. Accordingly, a model of fault diagnosis based on VPRS (variable precision rough set) theory is proposed, the approach is realized by applying SOM (self-organizing map neural network) to discretize continuous attributes, using property of approximation dependency of VPRS to carry through attribute reduction and concluding decision-making rules. An example is given to explain how to use the fault diagnosis model.