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Volumn 3, Issue 3, 2009, Pages 171-178

Short term load demand forecasting in Indonesia by using double seasonal recurrent Neural networks

Author keywords

ARIMA; Double seasonal; Recurrent Neural Network; Short term electricity load demand

Indexed keywords


EID: 70349421297     PISSN: 19980140     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article
Times cited : (16)

References (16)
  • 3
    • 0029368511 scopus 로고
    • Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for short-term load forecasting
    • Chen, J.F., Wang, W.M., and Huang, C.M. 1995. Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for short-term load forecasting, Electric Power Systems Research, 34,187-196.
    • (1995) Electric Power Systems Research , vol.34 , pp. 187-196
    • Chen, J.F.1    Wang, W.M.2    Huang, C.M.3
  • 7
    • 0037191007 scopus 로고    scopus 로고
    • Short-term load forecasting based on artificial neural networks parallel implementation
    • Kalaitzakis, K., Stavrakakis, G.S., and Anagnostakis, E.M. 2002. Short-term load forecasting based on artificial neural networks parallel implementation. Electric Power Systems Research, 63, 185-196.
    • (2002) Electric Power Systems Research , vol.63 , pp. 185-196
    • Kalaitzakis, K.1    Stavrakakis, G.S.2    Anagnostakis3
  • 10
    • 70049118645 scopus 로고    scopus 로고
    • Unpublished PhD Dissertation, Department of Mathematics, Gadjah Mada University, Yogyakarta
    • Suhartono. 2007. Feedforward Neural Networks for Time Series Forecasting. Unpublished PhD Dissertation, Department of Mathematics, Gadjah Mada University, Yogyakarta.
    • (2007) Feedforward Neural Networks for Time Series Forecasting
    • Suhartono1
  • 11
    • 0043246006 scopus 로고    scopus 로고
    • Short-term electricity demand forecasting using double seasonal exponential smoothing
    • Taylor, J.W. 2003. Short-term electricity demand forecasting using double seasonal exponential smoothing, Journal of the Operational Research Society, 54, 799-805.
    • (2003) Journal of the Operational Research Society , vol.54 , pp. 799-805
    • Taylor, J.W.1
  • 12
    • 0034541159 scopus 로고    scopus 로고
    • Short term electric load forecasting via fuzzy neural collaboration
    • Tamimi, M. and Egbert, R. 2000. Short term electric load forecasting via fuzzy neural collaboration. Electric Power Systems Research, 56, 243-248.
    • (2000) Electric Power Systems Research , vol.56 , pp. 243-248
    • Tamimi, M.1    Egbert, R.2
  • 13
    • 31744444183 scopus 로고    scopus 로고
    • A comparison of univariate methods for forecasting electricity demand up to a day ahead
    • Taylor, J.W., Menezes, L.M., and McSharry, P.E. 2006. A comparison of univariate methods for forecasting electricity demand up to a day ahead. International Journal of Forecasting, 22, 1-16.
    • (2006) International Journal of Forecasting , vol.22 , pp. 1-16
    • Taylor, J.W.1    Menezes, L.M.2    McSharry, P.E.3
  • 14
    • 0037379803 scopus 로고    scopus 로고
    • A hybrid learning for neural networks applied to short term load forecasting
    • Topalli, A.K. and Erkmen, I. 2003. A hybrid learning for neural networks applied to short term load forecasting, Neurocomputing, 51, 495-500.
    • (2003) Neurocomputing , vol.51 , pp. 495-500
    • Topalli, A.K.1    Erkmen, I.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.