S TE 0805351 BIBIOGRAPHY
42
DAFTAR PUSTAKA
Bai-Ling Zhang, Zhao-Yang Dong, 2001. “ An adaptive neural-wavelet model
for short term load forecasting”. Electric power System Research.
Barzamini, R., Menhaj, M., B., Khosravi, A., Kamalvand, S., H., 2005. “ Short
Term Load Forecasting for Iran Nation Power System and Its Region
Using Multi Layer Perceptron and Fuzzy Inference Systems”.
Proceedings of International Joint Conference on Neural Networks,
Montreal, Canada, July 31 - August 4.
G.A. Adepoju, M.Sc. , S.O.A. Ogunjuyigbe, M.Sc. , and K.O. Alawode,
B.Tech., 2007. “ Application of Neural Network to Load Forecasting
in Nigerian Electrical Power System”. The Pacific Journal of Science
and Technology.
James W. Taylor, Lilian m. de Menezes, Patrick E. McSharry, 2006. “ A
Comparison of Univariate Methods for Forecasting Electricity
Demand Up to a Day Ahead”. international journal of Forecasting.
Kyung-Bin Song, Member, IEEE, Young-Sik Baek, Dug Hun Hong, and
Gilsoo Jang, Member, IEEE, 2005. “ Short-Term Load Forecasting for
the Holidays Using Fuzzy Linear Regression Method”. IEEE
Transsactions On Power System, VOL. 20, No.1, February.
K. Kalaitzakis, G.S. Stavrakakis, E.M. Anagnostakis, 2002. “ Short-term load
forecasting based on artificial neural networks parallel
implementation”. Electric Power Systems Research.
Kwang-Ho Kim, Jong-Keun Park, Kab-Ju Hwang, Sung-Hak Kim, 1995.
“ Implementation of Hybrid Short-term Load Forecasting System
Using Artificial Neural Networks and Fuzzy Expert Systems”. IEEE
Transactions on Power Systems.
Lacir J. Soares, Marcelo C. Medeiros, 2008. “ Modeling and Forecasting ShortTerm Electricity Load: A Comparison of Methods whit an Application
to Brazilian Data”. International Journal of Forecasting.
Luciano S. Moulin, Alexandre P. Alves da Silva, 1999. “ Neural Network
Based Short term Electric Load Forecasting with Confidence
Intervals”. Proceedings of the IV Brazilian Conference on Neural
Networks pp 007-012, July 20-22.
Undang Harman, 2013
Peramalan Beban Jangka Pendek Husus Hari Libur Berbasis Jaringan Syaraf Tiruan Dgn Algoritma
Back Propagation
Universitas Pendidikan Indonesia | repository.upi.edu
43
M. A. El-Sharkawi, S. Oh, R. J. Marks, M. J. Damborg, 1991. “ Short Term
Electric Load Forecasting Using An Adaptively Trained Layered
Perceptron”. Departement of Electrical Engineering University of
Washington.
Marsudi, Djiteng. (2006). Operasi Sistem Tenaga Listrik. Yogyakarta: Graha
Ilmu.
Mataram Made I, 2008. “ Peramalan Beban Hari Libur Menggunakan Artificial
Neural Network”. Kampus Bukit Jimbaran, Bali, 80361.
Nguyen-Vu Truong, Liuping Wang, Peter K.C. Wong, 2008. “ Modelling and
Short Term forecasting of daily peak power demand in Victoria using
two dimensional wavelet based SDP models”. Electrical Power and
Energy Systems.
Rafal weron, Adam Misiorek, 2008. “ Forecasting spot electricity prices: A
Comparison of Parametric and semiparametric time series models”.
International Journal of Forecasting.
RM Andri, 2010, Studi Model Prakiraan Beban Listrik Harian Menggunakan
Metode Moving Average dan Metode Backpropagation , Pendidikan
Teknik Elektro Fakultas Pendidikan Teknologi dan Kejuruan UPI.
Saied S. Sharif, James H. Taylor, 1999. “Short-Term Load Forecasting by
Feed-Forward Neural Networks”. Department of Electrical and
Computer Engineering, University of New Brunswick.
Siang, Jong Jek. (2005). Jaringan Syaraf Tiruan dan Pemogramannya dengan
MATLAB, Yogyakarta: Andi
T. Yalcinoz, U. Eminoglu, 2005. “ Short term and medium term power
distribution load forecasting by neural network”. Energy Conversion
and Management.
Ying Chen, Peter B. Luh, Fellow, IEEE, Che Guan, Yige Zhao, Laurent D.
Michel, Matthew A. Coolbeth, Peter B. Friedland, and Stephen J.
Rourke, Senior Member, IEEE , 2010. “ Short-Term Load
Forecasting: Similar Day-Based Wavelet Neural Networks”. IEEE
Transactions on Power Systems, Vol, 25, NO.1, February.
Zainab H. Osman, Mohamed L. Awad and Tawfik K. Mahmoud, 2009. “Neural
Network Based Approach for Short Term Load Forecasting”. IEEE.
Undang Harman, 2013
Peramalan Beban Jangka Pendek Husus Hari Libur Berbasis Jaringan Syaraf Tiruan Dgn Algoritma
Back Propagation
Universitas Pendidikan Indonesia | repository.upi.edu
DAFTAR PUSTAKA
Bai-Ling Zhang, Zhao-Yang Dong, 2001. “ An adaptive neural-wavelet model
for short term load forecasting”. Electric power System Research.
Barzamini, R., Menhaj, M., B., Khosravi, A., Kamalvand, S., H., 2005. “ Short
Term Load Forecasting for Iran Nation Power System and Its Region
Using Multi Layer Perceptron and Fuzzy Inference Systems”.
Proceedings of International Joint Conference on Neural Networks,
Montreal, Canada, July 31 - August 4.
G.A. Adepoju, M.Sc. , S.O.A. Ogunjuyigbe, M.Sc. , and K.O. Alawode,
B.Tech., 2007. “ Application of Neural Network to Load Forecasting
in Nigerian Electrical Power System”. The Pacific Journal of Science
and Technology.
James W. Taylor, Lilian m. de Menezes, Patrick E. McSharry, 2006. “ A
Comparison of Univariate Methods for Forecasting Electricity
Demand Up to a Day Ahead”. international journal of Forecasting.
Kyung-Bin Song, Member, IEEE, Young-Sik Baek, Dug Hun Hong, and
Gilsoo Jang, Member, IEEE, 2005. “ Short-Term Load Forecasting for
the Holidays Using Fuzzy Linear Regression Method”. IEEE
Transsactions On Power System, VOL. 20, No.1, February.
K. Kalaitzakis, G.S. Stavrakakis, E.M. Anagnostakis, 2002. “ Short-term load
forecasting based on artificial neural networks parallel
implementation”. Electric Power Systems Research.
Kwang-Ho Kim, Jong-Keun Park, Kab-Ju Hwang, Sung-Hak Kim, 1995.
“ Implementation of Hybrid Short-term Load Forecasting System
Using Artificial Neural Networks and Fuzzy Expert Systems”. IEEE
Transactions on Power Systems.
Lacir J. Soares, Marcelo C. Medeiros, 2008. “ Modeling and Forecasting ShortTerm Electricity Load: A Comparison of Methods whit an Application
to Brazilian Data”. International Journal of Forecasting.
Luciano S. Moulin, Alexandre P. Alves da Silva, 1999. “ Neural Network
Based Short term Electric Load Forecasting with Confidence
Intervals”. Proceedings of the IV Brazilian Conference on Neural
Networks pp 007-012, July 20-22.
Undang Harman, 2013
Peramalan Beban Jangka Pendek Husus Hari Libur Berbasis Jaringan Syaraf Tiruan Dgn Algoritma
Back Propagation
Universitas Pendidikan Indonesia | repository.upi.edu
43
M. A. El-Sharkawi, S. Oh, R. J. Marks, M. J. Damborg, 1991. “ Short Term
Electric Load Forecasting Using An Adaptively Trained Layered
Perceptron”. Departement of Electrical Engineering University of
Washington.
Marsudi, Djiteng. (2006). Operasi Sistem Tenaga Listrik. Yogyakarta: Graha
Ilmu.
Mataram Made I, 2008. “ Peramalan Beban Hari Libur Menggunakan Artificial
Neural Network”. Kampus Bukit Jimbaran, Bali, 80361.
Nguyen-Vu Truong, Liuping Wang, Peter K.C. Wong, 2008. “ Modelling and
Short Term forecasting of daily peak power demand in Victoria using
two dimensional wavelet based SDP models”. Electrical Power and
Energy Systems.
Rafal weron, Adam Misiorek, 2008. “ Forecasting spot electricity prices: A
Comparison of Parametric and semiparametric time series models”.
International Journal of Forecasting.
RM Andri, 2010, Studi Model Prakiraan Beban Listrik Harian Menggunakan
Metode Moving Average dan Metode Backpropagation , Pendidikan
Teknik Elektro Fakultas Pendidikan Teknologi dan Kejuruan UPI.
Saied S. Sharif, James H. Taylor, 1999. “Short-Term Load Forecasting by
Feed-Forward Neural Networks”. Department of Electrical and
Computer Engineering, University of New Brunswick.
Siang, Jong Jek. (2005). Jaringan Syaraf Tiruan dan Pemogramannya dengan
MATLAB, Yogyakarta: Andi
T. Yalcinoz, U. Eminoglu, 2005. “ Short term and medium term power
distribution load forecasting by neural network”. Energy Conversion
and Management.
Ying Chen, Peter B. Luh, Fellow, IEEE, Che Guan, Yige Zhao, Laurent D.
Michel, Matthew A. Coolbeth, Peter B. Friedland, and Stephen J.
Rourke, Senior Member, IEEE , 2010. “ Short-Term Load
Forecasting: Similar Day-Based Wavelet Neural Networks”. IEEE
Transactions on Power Systems, Vol, 25, NO.1, February.
Zainab H. Osman, Mohamed L. Awad and Tawfik K. Mahmoud, 2009. “Neural
Network Based Approach for Short Term Load Forecasting”. IEEE.
Undang Harman, 2013
Peramalan Beban Jangka Pendek Husus Hari Libur Berbasis Jaringan Syaraf Tiruan Dgn Algoritma
Back Propagation
Universitas Pendidikan Indonesia | repository.upi.edu