Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification $E$-Algorithm

@article{Xu2007PowerDF,
  title={Power Distribution Fault Cause Identification With Imbalanced Data Using the Data Mining-Based Fuzzy Classification  \$E\$-Algorithm},
  author={Le Xu and Mo-yuen Chow and L. S. Taylor},
  journal={IEEE Transactions on Power Systems},
  year={2007},
  volume={22},
  pages={164-171}
}
Power distribution systems have been significantly affected by many outage-causing events. Good fault cause identification can help expedite the restoration procedure and improve the system reliability. However, the data imbalance issue in many real-world data sets often degrades the fault cause identification performance. In this paper, the E-algorithm, which is extended from the fuzzy classification algorithm by Ishibuchi to alleviate the effect of imbalanced data constitution, is applied to… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 23 references

Data mining for distribution system fault classification

  • H. M. Dola, B. H. Chowdhury
  • Proc. Annu. North Amer. Power Symp., 2005, pp…
  • 2005
1 Excerpt

Data mining for distribution system fault classification , ” in

  • T. L. B. Tseng
  • Proc . Annu . North Amer . Power Symp .
  • 2005

Rough set theory for data mining for fault diagnosis on distribution feeder

  • J. T. Peng, C. F. Chien, T.L.B. Tseng
  • Proc. Inst. Elect. Eng., Gen., Transm., Distrib…
  • 2004
1 Excerpt

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