Search results

The purpose of this paper is to propose a new grey system model used for prediction.

It had been proven that the GM(1,1) model is a biased exponential model, the model is fit for non‐negative raw data, which accord with or basically accord with the exponential form and do not have a quick growth rate. Based on the results, an unbiased GM(1,1) model was proposed. With the method of transforming every datum of raw data sequence into its 2‐th root, a new data sequence from the raw data sequence can be produced. The new data sequence is used to establish an unbiased GM(1,1) model and statistical experiments and a practical example in load forecasting are given in the paper.

The results of statistical experiments and a practical example in load forecasting show the proposed method is effective in increasing the accuracy of the model.

The model exposed in the paper can be used for constructing models of prediction in many fields such as agriculture, electric power, IT, transportation, economics, management, etc.

The paper succeeds in proposing a modified unbiased GM(1,1) model that has high accuracy. The model is applied to the field of load forecasting and the results show the model is better than the unbiased GM(1,1) model. The model proposed has great theoretical and practical value.