Predictive maintenance model based on multisensor data fusion of hybrid fuzzy rough set theory feature selection and stacked ensemble for fault classification

HIGHLIGHTS

• who: Albert Buabeng and colleagues from the Faculty of Engineering, Mathematical Sciences Department, University of Mines and Technology have published the Article: Predictive Maintenance Model Based on Multisensor Data Fusion of Hybrid Fuzzy Rough Set Theory Feature Selection and Stacked Ensemble for Fault Classification, in the Journal: Mathematical Problems in Engineering of 29/06/2022
• what: This study proposes a systematic predictive maintenance framework based on the hybrid multisensor fusion technique of fuzzy rough set feature selection and stacked ensemble for the efficient classification of fault conditions characterised by uncertainties. Considering the fact that the . . .
  

   

  

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