An extended grey forecasting model for omnidirectional forecasting considering data gap difference

作者：Li Der Chiang^*; Chang Che Jung; Chen Wen Chih; Chen Chien Chih

来源：Applied Mathematical Modelling, 2011, 35(10): 5051-5058.

DOI：10.1016/j.apm.2011.04.006

• Accumulating generation
• Competitive business
• Data gap
• Fatigue Limit
• Forecasting accuracy
• Forecasting models
• Forecasting techniques
• Grey forecasting model
• Grey Model
• Grey system theory
• Grey theory
• Incomplete information
• Prediction methods
• Short term prediction
• Small data set
• Small samples
• Temperature changes

To achieve effective and efficient decision making in a highly competitive business environment, an enterprise must have an appropriate forecasting technique that can meet the requirements of both timeliness and accuracy. Accordingly, in the early stages, building a forecasting model with incomplete information and limited samples is very important to a business. Grey system 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 purpose of this study is to come up with an improved forecasting model based on the concept of this theory to enlarge the applicability of the grey forecasting model in various situations. By extending the data transforming approach, this method generalizes a building procedure for the grey model to grasp the data outline and information trend. Specifically, a novel inverse accumulating generation operator is developed to enable omnidirectional forecasting. The research utilizes observations of the titanium alloy fatigue limit along with temperature changes as raw data to verify the performance of the proposed method. The experimental results show that not only can this method expand the application scope of the grey forecasting model, but also improve its forecasting accuracy.

• 出版日期2011