TY  - JOUR
AB  - Purpose– To combine the forecasting by single method using influence information fully, other than regular combined methods only focusing on historical forecasting errors.Design/methodology/approach– To combine the single methods based on the analysis of improved gray correlation, with more related information being considered to enhance the price forecasting precision, such as the trend of the prices, the historical forecasting errors, and the temporal influence factors on prices.Findings– A case of PJM market of USA shows that the proposed method has better performance than any other combined methods, and all single models as well.Research limitations/implications– The combined performance depends on the forecasting precision of single methods, and the correlation between the single methods, as well as the number of single method that to be combined.Practical implications– It is a novel idea for combined method to forecasting the time series data, such as electricity prices, electric power loads.Originality/value– The proposed method considers all the following factors: the similarity between the trends of the single forecasting, the errors of the single models and the temporal influence.
VL  - 38
IS  - 3/4
SN  - 0368-492X
DO  - 10.1108/03684920910944047
UR  - https://doi.org/10.1108/03684920910944047
AU  - Da Liu
AU  - Dongxiao Niu
AU  - Yuanyuan Li
AU  - Guanjuan Chen
ED  - Mian‐yun Chen
ED  - Yi Lin
ED  - Hejing Xiong
PY  - 2009
Y1  - 2009/01/01
TI  - Combined models for day‐ahead electricity price forecasting based on improved gray correlation methodology
T2  - Kybernetes
PB  - Emerald Group Publishing Limited
SP  - 354
EP  - 361
Y2  - 2024/09/19
ER  -