Abstract

By establishing a regional green innovation system, realizing the integrated development of industries across administrative divisions, and developing emerging industries, continuation industries, and resource reuse industries are effective ways to realize the transformation of economic development mode. In the process of shifting from the industrial economy of the industrial society to the industrial economy of the information society, green industry informatization is an inevitable requirement for realizing industrial restructuring and industrial upgrading, improving the core competitiveness of green enterprises, and a necessary condition for realizing regional national economic informatization. Data mining technology can discover and extract hidden, novel, meaningful and understandable information and patterns from a large amount of data, and realize the transformation from simple data to information to knowledge. According to the general requirements of data mining technology and the characteristics of the green industry field, this research constructed a system framework for green industry data mining, discussed key issues such as data preparation and data selection in data mining of green industry. Meanwhile, using data mining software SAS and Malmquist index as implementation tools, the basic theories and methods of green industry data mining were applied to the innovation evaluation of my country’s green industry. The results showed that data mining technology had its unique advantages in dealing with the massive data of the green industry. It can not only quickly realize the diversified statistical analysis of the massive data in the green industry, but also display it to users with rich graphics, which is conducive to the interpretation and understanding of the analysis results.

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