%0 Journal Article %1 Dong:1997:EPSR %A Dong, Gyu Lee %A Byong, Whi Lee %A Soon, Heung Chang %D 1997 %J Electric Power Systems Research %K Electric Forecasting, algorithms, demand genetic programming, %N 1 %P 17--22 %R doi:10.1016/S0378-7796(96)01125-X %T Genetic programming model for long-term forecasting of electric power demand %U http://www.sciencedirect.com/science/article/B6V30-3WDCJBW-3/2/c71881481512566c7b47d81606334180 %V 40 %X Genetic programming (GP) involves finding both the functional form and the numeric coefficients for the model. So it does not require the assumption of any functional relationship between dependent and independent variables. The use of GP for solving long-term forecasting of the electric power demand problem is discussed; several cases which have different combinations of terminal sets and functional sets were investigated. The results of annual forecasting of electric power demand are presented for various cases using the GP model. The GP model is compared with the regression model.

@article{Dong:1997:EPSR, abstract = {Genetic programming (GP) involves finding both the functional form and the numeric coefficients for the model. So it does not require the assumption of any functional relationship between dependent and independent variables. The use of GP for solving long-term forecasting of the electric power demand problem is discussed; several cases which have different combinations of terminal sets and functional sets were investigated. The results of annual forecasting of electric power demand are presented for various cases using the GP model. The GP model is compared with the regression model.}, added-at = {2008-06-19T17:35:00.000+0200}, author = {Dong, Gyu Lee and Byong, Whi Lee and Soon, Heung Chang}, biburl = {https://www.bibsonomy.org/bibtex/2bd2a8c01bb73bad10ae0aa78bbb8af5a/brazovayeye}, doi = {doi:10.1016/S0378-7796(96)01125-X}, interhash = {0054f6acf7e267e7226b238c990ca450}, intrahash = {bd2a8c01bb73bad10ae0aa78bbb8af5a}, journal = {Electric Power Systems Research}, keywords = {Electric Forecasting, algorithms, demand genetic programming,}, number = 1, owner = {wlangdon}, pages = {17--22}, timestamp = {2008-06-19T17:38:51.000+0200}, title = {Genetic programming model for long-term forecasting of electric power demand}, url = {http://www.sciencedirect.com/science/article/B6V30-3WDCJBW-3/2/c71881481512566c7b47d81606334180}, volume = 40, year = 1997 }