Artificial neural network enhanced by gap statistic algorithm applied for bad data detection of a power system

Shyh Jier Huang, Jeu Min Lin

Research output: Contribution to conferencePaper

7 Citations (Scopus)

Abstract

In this paper, a gap statistic algorithm (GSA) is applied for the bad data analysis. In the method, GSA is employed for the enhancement of neural networks. Because the number of cluster can be determined via GSA more effectively, this integrated approach is beneficial for the localization of the group of bad data. The proposed approach was validated through the data collected from the operation of a power system. Test results pointed to the feasibility of the method for the applications considered.

Original languageEnglish
Pages764-768
Number of pages5
Publication statusPublished - 2002 Dec 1
EventIEEE/PES Transmission and Distribution Conference and Exhibition 2002 : Asia Pacific - Yokahama, Japan
Duration: 2002 Oct 62002 Oct 10

Other

OtherIEEE/PES Transmission and Distribution Conference and Exhibition 2002 : Asia Pacific
CountryJapan
CityYokahama
Period02-10-0602-10-10

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All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Huang, S. J., & Lin, J. M. (2002). Artificial neural network enhanced by gap statistic algorithm applied for bad data detection of a power system. 764-768. Paper presented at IEEE/PES Transmission and Distribution Conference and Exhibition 2002 : Asia Pacific, Yokahama, Japan.