Empirical Cloud Computing Remote Human Resource Work Efficiency System Based on Data Mining

In order to improve the dynamic monitoring ability of power grid human resource management system, fuzzy information cluster analysis technology is used to study the dynamic monitoring technology of power grid human resources. This paper establishes a modern HR management system based on cloud computing. The virtual architecture layer mainly collects entities and virtual computing resources in multiple Spaces, and integrates these resources into a dynamically adjustable database to realize the physical storage and transmission of data. The row and column decisions of the situation are obtained through multiple objective situation decisions. Using multiple target situation decision matrix, the optimal situation is selected for personnel allocation and fed back to the display layer. The distribution structure model of power consumption human resources is established and the distribution cluster center of power consumption human resources is obtained. In this paper, the multi-dimensional time scale features of personnel data are examined by clustering method, and the automatic identification and fuzzy extraction of personnel data are realized. The state equation of the model is obtained by simulating the model. The accuracy and rapidity of this algorithm in human resource data monitoring are verified by statistical analysis of power grid human resource data. The research results of this paper provide an effective means for the effective utilization of power grid human resources.