TY  - JOUR
AB  - Purpose– The purpose of this paper is to present a method to accurately forecast the tendency of the gross amount of energy sources consumption of the country and construct a new kind of algorithm for forecasting that synthesizes the advantages of the grey model, Markov chains, and least square method.Design/methodology/approach– With the application of this new algorithm, this paper have forecasted the trend of the gross amount of energy sources consumption of the country and come to the conclusions that the new algorithm is more precise than the grey model. It is proved that the improved grey‐Markov chain algorithm is effective and can be used by authorities to make decision.Findings– It was found that combining the grey model, Markov chains, and least square method, can be a new algorithm for forecasting the trendency of the gross amount of energy sources consumption.Research limitations/implications– The new algorithm is only suitable for the short‐term forecast.Originality/value– The grey forecasting method reflects the overall tendency of primitive data sequence of the gross amount of energy source, and the Markov chain forecasting method reflects the effect of the random fluctuation. The least square method reflects the tendency of increase. The new algorithm is more precise than the grey model.
VL  - 38
IS  - 3/4
SN  - 0368-492X
DO  - 10.1108/03684920910944010
UR  - https://doi.org/10.1108/03684920910944010
AU  - Zhijun Li
AU  - Weiwei Wang
AU  - Mian‐yun Chen
ED  - Mian‐yun Chen
ED  - Yi Lin
ED  - Hejing Xiong
PY  - 2009
Y1  - 2009/01/01
TI  - Improved grey‐Markov chain algorithm for forecasting
T2  - Kybernetes
PB  - Emerald Group Publishing Limited
SP  - 329
EP  - 338
Y2  - 2024/09/22
ER  -