Papers by Keyword: Improved GM(1,1)

Abstract: In this paper, a control system based on the prediction of processing flow in Abrasive flow machining is designed. In this system,flow is predicted by an improved GM(1,1) model in conformation of background value. Combined with fuzzy control system, it can adapt the pressure to meet the processing requirement automatically. Experiments proved that the improved GM(1,1) model can predict the processing flow accuratly, and the fuzzy control system based on grey prediction can improve the machining accuracy of micro-hole AFM effectively.

Abstract: Accurate prediction of the order quantity for the next period is very important for the enterprise to enhance the commercial competitive advantage in a highly competitive business environment. GM(1,1) theory is one of the prediction methods that can be built with a small sample and yet has a strong ability to make short-term predictions. The objective of the paper is to propose a order quantity prediction model which is combined the improved GM(1,1) model and Markov chain model .The effectiveness of the proposed approach to the order prediction is demonstrated using real-world data from a famous company in Liuzhou.The results indicate that the method of prediction is satisfying.

Abstract: The forecasting precision of GM(1,1) is very low, when the data sequence is not smooth. The logarithm smoothing is used for the original data sequence. Considering the low precision caused by overlarge and forecasting gray interval for gray modeling, A novel method is proposed for power load forecasting: weighted forecasting method of gray related degree with revised parameter and logarithm smoothing. The method can make various factors weaken or counteracted and prevent the forecasting data from too fast increasing. The proposed model is demonstrated by a test in a certain area. The result shows that the method is effective both in theory and in practice.