Research on data value evaluation of railway construction period based on ahp-grey clustering method

Xiaoqin Lian; Kai Yang; Chao Gao; Yanhua Wu; Zhibo Cheng; Yelan Wu; Yonggang Gong

doi:10.1117/12.2659981

9 December 2022 Research on data value evaluation of railway construction period based on ahp-grey clustering method

Xiaoqin Lian, Kai Yang, Chao Gao, Yanhua Wu, Zhibo Cheng, Yelan Wu, Yonggang Gong

Proceedings Volume 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022); 1249204 (2022) https://doi.org/10.1117/12.2659981
Event: International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 2022, Wuhan, China

Abstract

In the hierarchical storage system, the data value needed to be evaluated to formulate rules data for hierarchical storage and migration. To further research the data hierarchical storage system in railway construction period and how to allocate the resources of the storage media with different performances, the researches on evaluation of the data value in railway construction period were pursued in the paper. Based on the business and non-business characteristics of the railway construction period, the evaluation indicator system of data value in railway construction period were designed, which can provide a comprehensive reference for the model. Combined with the quantification standard of evaluation indicators of data value in railway construction period designed in this paper, the complexity of indicator measurement can be reduced. In order to further improve the accuracy of model evaluation and meet data storage requirements, a comprehensive data value evaluation of railway construction period based on analytic hierarchy process (AHP)-grey clustering method was proposed. A simulation was carried out based on the data actually stored in a railway construction period, and the applicability of the model in the hierarchical storage system was proved by the geometric distribution of the results. In order to further verify the accuracy of the data value evaluation model proposed in this paper, its evaluation results were compared with that of the traditional model based on the same group of data. Experimental results shown that the data value model proposed in this paper was more accurate and adaptable than the traditional model in railway construction period, and can better meet the application requirements of the actual railway hierarchical storage system.

Citation Download Citation

Xiaoqin Lian, Kai Yang, Chao Gao, Yanhua Wu, Zhibo Cheng, Yelan Wu, and Yonggang Gong "Research on data value evaluation of railway construction period based on ahp-grey clustering method", Proc. SPIE 12492, International Workshop on Automation, Control, and Communication Engineering (IWACCE 2022), 1249204 (9 December 2022); https://doi.org/10.1117/12.2659981

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KEYWORDS

Data modeling

Data storage

Computer security

Performance modeling

Systems modeling

Databases

Associative arrays

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