Dr. Yun Li Profile

Dr. Yun Li

at China Industrial Control Systems Cyber Emergency Response Team

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Proceedings Article | 3 October 2022 Paper

A new data process framework of industrial big data based on feature selection

Fengjuan Xu, Haitong He, Jianlei Gao, Tianyu Gong, Yaobing Li, Yun Li

Proceedings Volume 12290, 1229012 (2022) https://doi.org/10.1117/12.2641163

KEYWORDS: Data storage, Data processing, Feature extraction, Data modeling, Data analysis, Feature selection, Control systems, Binary data, Information technology, Data mining

Read Abstract +

The continuously updated and widely applied information technology and internet technology make the amount of data increase with an unimaginable speed. Subsequently, industries have also entered into the “Digital Times”, which brings challenges and opportunities for industrialization. Through industrial big data government technology, we can continuously improve the level of industrial intelligence, the management efficiency and the production efficiency of enterprises, so as to improve the competitiveness of enterprises and the country. However, in the face of this large number of industrial big data with complex and diverse data characteristics, the application of traditional data processing methods in industrial big data government is not applicable, especially in the condition of valuable and scarce computing resources. A new proper data process framework, in this paper, is proposed for industrial data, whose principle is to reasonably select data features by utilizing a max-relevance min-redundancy (mrmr) algorithm that considering the relationship between data characteristics. The effect is verified on a series of industrial datasets. And the experiments results can effectively improve the utilization and analysis efficiency of data, reduce the difficulty of data processing, improve the data storage efficiency and reduce the data storage space.

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