Cargando…
Application of Data Mining Technology in Enterprise Green Innovation Model Construction and Path Analysis
Since sustainable development has become the dominant mode of human development at the present stage, green technology has received more and more attention under this background. The development of green technology has become an important means to achieve sustainable development. Green technological...
Autor principal: | |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9300339/ https://www.ncbi.nlm.nih.gov/pubmed/35875774 http://dx.doi.org/10.1155/2022/7194171 |
Sumario: | Since sustainable development has become the dominant mode of human development at the present stage, green technology has received more and more attention under this background. The development of green technology has become an important means to achieve sustainable development. Green technological innovation is a kind of technological innovation. However, because the goal of green technological innovation is different from that of traditional technological innovation, the dynamic mechanism of green technological innovation lies in the similarities and differences of traditional technological innovation. This paper focuses on data mining technology to design and optimize the enterprise green technology creation model. At present, clustering algorithm and association rule algorithm are important research contents in big data mining technology. Among them, the clustering algorithm refers to the process of grouping similar data objects in a large amount of data information, so that the approximate data information can be aggregated and clustered, which is convenient for data mining calculation. In the algorithm, the shortcomings of the original clustering algorithm, such as insufficient data processing and incomplete analysis, are improved, and the data processing is improved by 51.7%, which has a good processing effect on subsequent data preprocessing and dynamic incremental clustering. In the follow-up experiment, the role of green technology in corporate finance is reflected. |
---|