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Volumn 1, Issue , 2004, Pages 389-392

Applications of data mining technique for power system transient stability prediction

Author keywords

Data market; Data mining; Online analytical processing; Transient stability

Indexed keywords

ARTIFICIAL INTELLIGENCE; DATABASE SYSTEMS; ELECTRIC POWER SYSTEMS; INSTALLATION; LARGE SCALE SYSTEMS; MATHEMATICAL MODELS; NEURAL NETWORKS; SYSTEM STABILITY;

EID: 8644274894     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (11)

References (9)
  • 1
    • 0030288604 scopus 로고    scopus 로고
    • Transient stability assessment in longitudinal power system using artificial neural networks
    • Aboytes F and Ramirez R. "Transient stability assessment in longitudinal power system using artificial neural networks," IEEE Trans. on Power Systems, 11(4), pp.2003-2010. 1996.
    • (1996) IEEE Trans. on Power Systems , vol.11 , Issue.4 , pp. 2003-2010
    • Aboytes, F.1    Ramirez, R.2
  • 6
    • 0030211964 scopus 로고    scopus 로고
    • Bagging predictors
    • Breiman L " Bagging Predictors," Machine Learning, 1996 24(2) pp,123-140
    • (1996) Machine Learning , vol.24 , Issue.2 , pp. 123-140
    • Breiman, L.1
  • 9
    • 0003425664 scopus 로고    scopus 로고
    • Support vector machines for classification and regression
    • Image Speech and Intelligent Systems Research Group, University of Southampton
    • S. R. Gunn. "Support Vector Machines for Classification and Regression," Technical Report, Image Speech and Intelligent Systems Research Group, University of Southampton, 1997
    • (1997) Technical Report
    • Gunn, S.R.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.