Mutual information based input selection in neuro-fuzzy modeling for short term load forecasting of Iran National power system

2007 IEEE International Conference on Control and Automation, ICCA

Volumn , Issue , 2007, Pages 2710-2715

  Vahabie, A H ^a   Rezaei Yousefi, M M ^a   Araabi, B N ^a   Lucas, C ^a   Barghinia, S ^b   Ansarimehr, P ^b  

^a UNIVERSITY OF TEHRAN   (Iran)

^b NIROO RESEARCH INSTITUTE   (Iran)

Author keywords

Input selection; LoLiMoT; Mutual information; Neuro fuzzy modeling; Short term load forecasting

Indexed keywords

ECONOMIC ANALYSIS; INFORMATION ANALYSIS; MATHEMATICAL MODELS; NEURAL NETWORKS; TIME SERIES ANALYSIS;

INPUT SELECTION; MUTUAL INFORMATION; NEURO-FUZZY MODELING; SHORT TERM LOAD FORECASTING (STLF);

ELECTRIC LOAD FORECASTING;

EID: 44349138737     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCA.2007.4376854     Document Type: Conference Paper

References (16)

1. G. E. P. Box and G. M. Jenkins, Time Series Analysis Forecasting and Control, San Fransisco, CA Holden day, 1976.
2. S J Huang, and K. R. Shih, "Short-Term Load Forecasting via ARMA Model Identification Including Non-Gaussian Pprocess Considerations", IEEE Trans. Power Systems, vol. 18. pp. 673-679, May 2003.
3. A. Papoulis, and S. U. Pillai, Probability, Random Variables, and Stochastic Processes, Newyork McGraw-Hill, fourth edition, 2002
4. A K Sinha, "Short Term Load Forecasting Using Artificial Neural Networks", in Proc. Of IEEE Int. Conf. on Industrial Technology, Goa, India, 2000, vol. 1, pp. 548-553.
5. I. Drezga, and S Rahman, "Short Term Load Forecasting with Local ANN Predictors", IEEE Trans Power Systems, vol 14. pp 844-850. August 1999.
6. A. G Bakirtzis, J. B Theocharis, S. J. Kiatzis, and K.J. Satsios, "Short Term Load Forecasting using Fuzzy Neural Networks", IEEE Trans. Power Systems, vol. 10, pp. 1518-1524, 1995.
7. O. Nelles, Nonlinear system identification, Berlin: Springer-Verlag, 2001.
8. A. Gholipour, C. Lucas, B N. Araabi, and M Shafiee, "Solar activity forecast Spectral analysis and neurofuzzy prediction", Journal ofAymospheric and Solar Terrestrial Physics, vol. 67, Issue 6, pp. 595-603, April 2005.
9. A. S. Weigend, B. A. Huberman, D. E. Rumelhart, "Predicting the future: a connectionist approach", Int. Journal of Neural Systems, vol. 1, pp. 193-209, 1990.
10. C. E. Shannon, "A Mathematical Theory of Communication", The Bell System Technical, vol. 27, pp. 379-423, 623-656, July, October, 1948.
11. T. Cover, and J. Thomas, Elements of Information Theory, John Wiley, 1990.
12. D.W. Scott, Multivariable Density Estimation: Theory, Practice, and Visualization, New York: John Wiley, 1992.
13. A. Kraskov, H. Stögbauer, and P. Grassberger, "Estimating mutual information", Physics. Review, E. 69, 066138, 2004.
14. F. Rossi, A. Lendasse, D. François, V. Wertz, and M. Verleysen, "Mutual information for the selection of relevant variables in spectrometric nonlinear modeling", Chemometrics and Intelligent Laboratory Systems, vol. 80, pp. 215-226, 2006.
15. R. Battiti, "Using Mutual Information for Selecting Features in Supervised Neural Net Learning", IEEE Trans. Neural Networks, vol. 5, pp. 537-550, July 1994.
16. A. A. Gorji, M. B. Menhaj, S. Barghinia, and P. Ansarimehr, "Fuzzy TSK model for Short Term Load Forecasting of Iran National Power System", Int. Conf on Power System Technology, Chongqing, China October, 2006.