Constructing the regional intelligent economic decision support system based on fuzzy C-mean clustering algorithm

Abstract

In order to help decision-making departments to know the information of regional economic development in time, the economic prediction and early warning model and economic policy simulation model of the decision-making system are constructed by analyzing the influencing factors of regional economy and taking the fuzzy C-means clustering as the main algorithm. Based on the data in the statistical yearbook, the corresponding module functions of the system are completed. Then, the system is applied to predict the recent economic development indicators. The results show that the forecasting data and the real data of the indicators are on the same level as a whole. When the growth rate of foreign trade export, fixed assets investment, fiscal expenditure and total retail sales of social consumer goods are increased by 1 percentage point, respectively, the GDP growth rate will increase by 0.105, 0.113, 0.134, 0.087 and 0.075 percentage points. The research suggests that the support system basically meets the requirements, can achieve the purpose of prediction, and has certain practicability.