Pillar Industry Judgment Based On Big Data

摘要

Compared with the traditional economic analysis of the industry, data analysis in the context of big data has more intuitive advantages. As to get the industrial feature attributes, the analysis of industry is segmented to three aspects, including comprehensive energy efficiency, economic contribution as well as energy conservation and environmental protection. After screening by gray correlation analysis, more influential feature attributes are finally obtained. The improved k-means clustering algorithm with adaptive weights is used to cluster industrial data. Through the example simulation, it is found that the objective display of the feature attribute data makes the advantages and disadvantages of pillar industry more intuitive, and can provide some guidance for the regional industrial construction.