Intelligent Analysis of The Causes for China’s Regional Economic Growth Based on FCA

In order to study the imbalance and difference of its development comprehensively and dynamically, and acquire more correct analysis results, this paper establishes the application model of clustering analysis method based on data mining in regional economic research. According to the design principle of evaluation index, taking 13 cities in Guangdong Province as samples, we propose a practical regional evaluation index system. FCA is used as the compression representation of frequent mode to perform intelligent comprehensive evaluation on the cities in economic zone. The size of the problem can be reduced by dividing the search space. In the case study, the macro-economic indicators and data of the Regional Economic Yearbook are combined, and the key factors affecting the regional economy are found out by using Polyalyst and MATLAB. The final analysis and statistical results show that the clustering results based on the level of regional economic development are effective and can provide quantitative basis for analyzing the development status and characteristics of regional economy in China.