Application of probabilistic rough set models to mechanical fault diagnosis
Cai Rui-ying · Computer Engineering and Applications Journal · 2009
In engineering application,for different reasons and various forms,mechanical fault diagnosis does not achieve desirable results.Probabilistic rough set model overcomes the lack of Pawlak rough set model in decision making under uncertainty knowledge.The model can make full use of statistical information around boundaries and give a completed description to given concepts,therefore it can extract decision-making rules with confirmed factors.The paper first explains probabilistic rough set model and introduces attribute reduction of the model,then describes probabilistic rough set model in the mechanical fault diagnosis application,which is about Bayes decision problem.Finally,the instance validates the feasible application of probabilistic rough set in mechanical fault diagnosis.