Business Cycle Index Forecasting of Grey Model Optimized by Genetic Algorithm

Business cycle forecasting is the premise and foundation of strategy-making, plan-making and decision-making. According to business cycle index forecasting method, due to small sample data of leading indicator, it is difficult to determine changes in trends of business cycle fluctuation. Leading index is forecasted to extend its sample by the gray model. In order to overcome using least squares method to determine Development Coefficient and Endogenous Grey Action of GM(1,1), an optimization grey model based on Genetic Algorithm is proposed. For the propose of verification the validity of the method, the proposed method is applied to forecast business cycle index of China macro economy, and compared with GM(1,1). The experimental result shows the feasibility and effectiveness of the method.