Grey GM(1, 1) model with function‐transfer method and application to energy consuming prediction

The ability to forecast a trend is very important in energy consumption prediction and energy production planning. The principle, under which the grey systems theory is applied in our energy consumption prediction, is that the forecasting system can be considered as a grey system. In such a system, unknown system's information can be determined by using known information. Here, the known information consists of energy consumption data, development trend in the consumption system. Based on our study, we eventually make forecast and decisions regarding possible future development. Our method is a whitenization process of a grey course. The model developed is based on the division method established for general data modelling and estimation of parameters of GM(1,1) its standard error coefficient that was applied to judge the accuracy height of the model was put forward; further, the function transform to forecast energy consuming trend and assess GM(1, 1) parameter was established. These two models need not pre‐process the primitive data. It was not only suited for equal interval data modeling, but also for non‐equal interval data modeling. Its calculation was simple and used conveniently, and the oil consumption per unit output analysis was taken as an example. The example showed that the two models were simple and practical, it was worth expanding and applying in the energy consuming prediction and energy programming.