A hierarchical neural model with time windows in long-term electrical load forecasting

Neural Computing and Applications

Volumn 16, Issue 4-5, 2007, Pages 465-470

  Carpinteiro, Otávio A S ^a   Lima, Isaías ^a   Leme, Rafael C ^a   De Souza, Antonio C Zambroni ^a   Moreira, Edmilson M ^a   Pinheiro, Carlos A M ^a  

^a FEDERAL UNIVERSITY OF ITAJUBÁ   (Brazil)

Author keywords

Electrical load forecasting; Neural networks; Time series prediction

Indexed keywords

EID: 34249070122     PISSN: 09410643     EISSN: None     Source Type: Journal    
DOI: 10.1007/s00521-006-0072-8     Document Type: Article

References (18)

1. Makridakis S, Hibon M (2000) The M3-Competition: results, conclusions and implications. Int J Forecast 16:451-476
2. Kangas J (1994) On the analysis of pattern sequences by self-organizing maps. PhD Thesis, Laboratory of Computer and Information Science, Helsinki University of Technology, Rakentajanaukio 2 C, SF-02150, Finland
3. Chappell GJ, Taylor JG (1993) The temporal Kohonen map. Neural Netw 6:441-145
4. Barreto GA, Araújo APR (2001) Time in self-organizing maps: an overview of models. Int J Comput Res Spec Issue Neural Netw Past Present Future 10(2):139-179
5. Kremer SC (2001) Spatio-temporal connectionist networks: a taxonomy and review. Neural Comput 13(2):249-306
6. Barreto GA, Araújo APR, Kremer SC (2003) A taxonomy for spatiotemporal connectionist networks revisited: the unsupervised case. Neural Comput 15(6):1255-1320
7. Papalexopoulos A, Hao S, Peng T (1994) An implementation of a neural network based load forecasting model for the EMS. IEEE Trans Power Syst 9(4):1956-1962
8. Bakirtzis A, Petridis V, Klartzis S, Alexiadis M, Maissis A (1996) A neural network short-term load forecasting model for the Greek power system. IEEE Trans Power Syst 11(2):858-863
9. Khotanzad A, Afkhami-Rohani R, Maratukulam D (1998) ANNSTLF - artificial neural network short-term load forecaster - generation three. IEEE Trans Power Syst 13(4):1413-1422
10. Hippert H, Pedreira C, Souza R (2001) Neural networks for short-term load forecasting: a review and evaluation. IEEE Trans Power Syst 16(1):44-55
11. Kermanshahi B (1998) Recurrent neural network for forecasting next 10 years load of nine Japanese utilities. Neurocomputing 23:125-133
12. Kohonen T (2001) Self-organizing maps, 3rd edn. Springer, Berlin Heidelberg New York
13. Galván IM, Isasi P (2001) Multi-step learning rule for recurrent neural models: an application to time series forecasting. Neural Process Lett 13:115-133
14. El-Sharkawi MA (2002) Internet web page http://www.ee.washington.edu/ class/559/2002spr/
15. Lo Z, Bavarian B (1991) Improved rate of convergence in Kohonen neural network. In: Proceedings of the international joint conference on neural networks, vol 2, pp 201-206
16. Lo Z, Fujita M, Bavarian B (1991) Analysis of neighborhood interaction in Kohonen neural networks. In: Proceedings of the 5th international parallel processing symposium, pp 246-249
17. Widrow G, Hoff ME (1960) Adaptive switching circuits. Institute of Radio Engineers, Western electronic show and convention, convention record, part 4
18. Sutton RS, Barto AG (1981) Toward a modern theory of adaptive networks: expectation and prediction Psychol Rev 88:135-170