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Volume 31 Issue 5
Oct.  2010
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LIU Yong-kuo, XIE Chun-li, XIA Hong. Research on Faults Data Processing and Attributes Reduction Arithmetic Based on Data Mining for Nuclear Power Plants[J]. Nuclear Power Engineering, 2010, 31(5): 24-27,38.
Citation: LIU Yong-kuo, XIE Chun-li, XIA Hong. Research on Faults Data Processing and Attributes Reduction Arithmetic Based on Data Mining for Nuclear Power Plants[J]. Nuclear Power Engineering, 2010, 31(5): 24-27,38.

Research on Faults Data Processing and Attributes Reduction Arithmetic Based on Data Mining for Nuclear Power Plants

  • Received Date: 2009-07-25
  • Rev Recd Date: 2009-10-20
  • Available Online: 2025-07-31
  • A distance standardized method is proposed considering the features of fault data of nuclear power plants and based on the knowledge discovery function of the data mining method,to standardize the data under different condition and of different order magnitudes.According to the characteristics of parameters,the parameters are dispersed using the alarm values,as a reference for the choice of the break points of the discrete data.The data are reduced using the concept lattice attribute reduction method,and thus the core attributes,relative necessary attributes and unnecessary attributes for fault diagnosis are obtained.The data in literature are calculated and the attributes are classified accurately.When the formal context is affirmatory,the fault can be diagnosed exactly using the core attributes.

     

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