[1]
Changhao Xia, Jian Wang, Karen McMenemy. Short, medium and long term load forecasting model and virtual load forecaster based on radial basis function neural networks, Electrical Power and Energy Systems 32 (2010) 743–750
DOI: 10.1016/j.ijepes.2010.01.009
Google Scholar
[2]
GORUCU F B , GUMRAH F. Evaluation and forecasting of gas consumption by statistical analysis. Energy Sources, 26 (3),2004,267-276.
DOI: 10.1080/00908310490256617
Google Scholar
[3]
VONDRACEKJ, PEL IKAN E and KONAR O. A statistical model for the estimation of natural gas consumption. Applied Energy, 85 (5) ,2008,pp.362-370
Google Scholar
[4]
Shahwan, T., Odening, M., Computational Intelligence in Economics and Finance, Springer, Berlin Heidelberg, New York, p.63–74, 2007.
Google Scholar
[5]
YANG Zhao, LIU Yan, MIAO Zhibin and LIU Zhenneng, Application of Neural network in Natural Gas Load Forecasting, Gas & Heat, 23(6),p.331—332, 2003.
Google Scholar
[6]
Dillon TS, Morsztyn K, Phua K. Short term load forecasting using adaptive pattern recognition and self-organizing techniques. In: Proceedings of the fifth world power system computation conference (PSCC-5), September 1975, Cambridge, paper 2.4/3, p.1–15.
Google Scholar
[7]
Kermanshahi B, Iwamiya H. Up to year 2020 load forecasting using neural nets. Int J Electr Power Energy Syst 2002;24:789–97
DOI: 10.1016/s0142-0615(01)00086-2
Google Scholar
[8]
Ghiassi M, Zimbra DK, Saidane H. Medium term system load forecasting with a dynamic artificial neural network model. Electr Power Syst Res 2006;76:302–16.
DOI: 10.1016/j.epsr.2005.06.010
Google Scholar
[9]
Carpinteiro OAS, Lemeb RC, Souza ACZ, Pinheiro CAM, Moreira EM. Long-term load forecasting via a hierarchical neural model with time integrators. Electr Power Syst Res 2007;77:371
DOI: 10.1016/j.epsr.2006.03.014
Google Scholar
[10]
Swales, G. S., & Yoon, Y. Applying artificial neural networks to investment analysis. Financial Analysts Journal, 48 (1992).78–80.
DOI: 10.2469/faj.v48.n5.78
Google Scholar