An Intelligence Optimized Rolling Grey Forecasting Model Fitting to Small Economic Dataset

作者：Liu, Li^*; Wang, Qianru; Liu, Ming; Li, Lian

来源：Abstract and Applied Analysis, 2014, 2014: 641514.

DOI：10.1155/2014/641514

• PREDICTION
• ALGORITHM
• OUTPUT

Grey system theory has been widely used to forecast the economic data that are often highly nonlinear, irregular, and nonstationary. The size of these economic datasets is often very small. Many models based on grey system theory could be adapted to various economic time series data. However, some of these models did not consider the impact of recent data or the effective model parameters that can improve forecast accuracy. In this paper, we proposed the PRGM(1,1) model, a rolling mechanism based grey model optimized by the particle swarm optimization, in order to improve the forecast accuracy. The experiment shows that PRGM(1,1) gets much better forecast accuracy among other widely used grey models on three actual economic datasets.

• 出版日期2014
• 单位合肥工业大学; 兰州大学; 西南大学