Affiliations: [a] School of Economics and Management, Heilongjiang Institute of Technology, Harbin, Heilongjiang, China
| [b] School of Economics and Management, Harbin University of Science and Technology, Harbin, Heilongjiang, China
Correspondence:
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Corresponding author. Shuqiang Liu, School of Economics and Management, Heilongjiang Institute of Technology, Harbin, Heilongjiang, China. E-mail: shuqiangliu@yeah.net.
Abstract: In general, there are a lot of uncertainties in uncertain information, natural language, and human knowledge. The conclusion can be better deduced by using an approximate reasoning method, while a fuzzy intelligent system can deal with uncertain data and rule evaluation information systems. In order to better explore diffusion and economic growth, this paper constructs a fuzzy intelligent system based on the DSGE model and uses this system to analyze diffusion and economic growth. In order to verify the feasibility of this system, we test the response time and accuracy of the system. In addition, we also use the system to simulate diffusion and economic growth. The results show that with the increase of the task amount, the gap between the actual response time and the expected response time of the fuzzy intelligent system based on the DSGE model increases. When the task quantity is 20, the expected response time is 2.31 and the actual response time is 2.24. When the task quantity is 40, the expected response time is 2.5 and the actual response time is 2.36. The larger the task quantity is, the faster the response time of a fuzzy intelligent system based on the DSEG model is. Therefore, the fuzzy intelligent system based on the DSEG model has good performance and can analyze diffusion and economic growth well.
Keywords: DSGE model, fuzzy intelligence system, system performance, diffusion, and economic growth
