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.
Chen Hongzhuan
NO. 29, Yudao Street, Nanjing, Jiangsu Province, PR. China
国际会议
2007年IEEE灰色系统与智能服务国际会议(2007 IEEE International Conference on Grey Systems and Intelligent Services)
南京
英文
2007-11-18（万方平台首次上网日期，不代表论文的发表时间）