Improving efficiency of artificial neural networks in electricity demand forecasting

IPEC 2003 - 6th International Power Engineering Conference

Volumn , Issue , 2003, Pages 1001-1006

  Lu, Xue Bing ^a   Sugianto, Ly Fie ^a  

^a MONASH UNIVERSITY   (Australia)

Author keywords

Backpropagation; Bayesian Regularisation; Levenberg Marquardt; Neural Networks; Quasi Newton; Scaled Conjugate Gradient; Steepest Descent

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; BACKPROPAGATION; DATA PROCESSING; ELECTRIC POWER SYSTEMS; FORECASTING; MATRIX ALGEBRA; NEURAL NETWORKS; OPTIMIZATION; PROBLEM SOLVING; VECTORS;

BAYESIAN REGULARIZATION; LEVENBERG-MARQUARDT; QUASI-NEWTON; SCALED CONJUGATE GRADIENT; STEEPEST DESCENT;

ELECTRIC INDUSTRY;

EID: 12744274873     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. R. Fletcher and C. M. Reeves, "Function Minimization by Conjugate Gradients," Computer Journal, vol. 7, pp. 149-154, 1964
2. F. D. Foresee and M. T. Hagan, "Gauss-Newton Approximation to Bayesian Regularization," Proceedings of the 1997 International Joint Conference on Neural Networks, pages 1930-1935, 1997.
3. M. T. Hagan, H. B. Demuth, M. H. Beale, Neural Network Design, PWS Publishing, Boston, MA, 1996
4. M. Henstenes, Conjugate Direction Methods in Optimization, Springer-Verlag, New York, 1980
5. H. S. Hippert, C. E. Pedreira, and R. C. Souza, "Neural Networks for Short-term Load Forecasting: A Review and Evaluation," IEEE Transactions on Power Systems, vol. 16, no. 1, pp. 44-55, 2001
6. R. Lamedica, A. Prudenzi, M. Sforna, M. Caciotta, and V.O. Ceneelli, "A Neural Network Based technique for Short-term forecasting of Anomalous Load Periods," IEEE Transactions on Power Systems, vol. 11, no. 4, pp. 1749-1756, 1996
7. K. Y. Lee, Y.T. Cha, and J.H. Park, "Short-term Load Forecasting Using An Artificial Neural Network," IEEE Transaction on Power Systems, vol. 7, no. 1, pp.124-132, 1992
8. D. J. C. Mackay, "Bayesian Interpolation," Neural Computation, vol.4, pp. 415-447, 1992
9. M. F. Moller, "A Scaled Conjugate Gradient Algorithm for Fast Supervised Learning," Neural Networks, vol. 6, pp. 525-533, 1993
10. L. E. Scales, Introduction to Nonlinear Optimisation, Macmillan, London, 1985
11. D. E. Rumelhart and J. L. McClelland, eds., Parallel Distributed Processing: Explanations in the Microstructure of Cognition, Vol. 1, Cambridge, MA:MIT Press, 1986
12. L. F. Sugianto, X. B. Lu, "Demand Forecasting in The Deregulated Market: A Bibliography Survey, AUPEC Conference Proceedings, Melbourne, Australia, 2002