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Safety portrait model of power workers based on GloVe and BiGRU

There are many types of operations in electric power field, which require high safety skills and safety awareness of electric power workers. In order to find out the weak links of power operation safety and improve the comprehensive quality of workers, this paper proposes a safety portrait model of power workers based on global vectors for word representation (GloVe) and bi-directional gate recurrent unit (BiGRU). Firstly, the proposed model adopts the Delphi method to set multidimensional labels for power workers and forms a text data set of power workers. Then, GloVe is used to construct word vector for the text data set of power workers. Finally, the constructed word vector is input into BiGRU network for training, and the labels of power workers to be analyzed are output. The results of the proposed model can help electric power corporations improve the comprehensive ability of workers in a targeted manner, and provide reference and guidance for personnel assessment, work order management, production control and other needs.