A fuzzy-grey optimizing prediction model based on the fuzzy membership function

This paper presents an optimizing fuzzy-grey prediction model in accordance with the phenomena that have different behaviors at different time. With the grey theory and fuzzy theory, we designed the ratio by the fuzzy membership function. Thus the ratio is variable to compensate for the limitation of GM(1,1) model, in which the ratio is a constant 0.5. Since some phenomena present different specific behaviors at different time, we constructed data groups to reduce the size of the targets and combined fuzzification techniques with the grey theory to develop a fuzzy grey prediction model as one of predicting function to predict the possible answer immediately and accurately. To demonstrate that our model is working correctly, we used this model to predict electricity every month in one year and got good results. The facts illustrate that the fuzzy-grey optimizing model shows many advantages as shown in this paper.