Design of Power Project Safety Management Application Integrating Natural Language Processing and Knowledge Graph
Safety management in power projects involves dealing with a substantial amount of textual data,and traditional meth-ods exhibit limitations in terms of efficiency and accuracy.Hence,this research integrates natural language processing to construct a knowledge graph for power project safety management.The results demonstrate outstanding performance of the proposed knowledge ex-traction model,with accuracy,recall,and F1 score reaching 0.94,0.91,and 0.92,respectively.Upon introducing the knowledge graph,the minimum time for resolving safety issues is reduced to 18.7 minutes.The average accuracy of decision-making improves to 91.46%,and there is a significant enhancement in the utilization of human resources and equipment,reaching 91.37%and 88.64%,respectively.The knowledge graph exhibits a knowledge update rate of 849 items per day,a knowledge base expansion speed of 857 items per day,and an average retrieval speed of 1048 times per second.A user satisfaction survey indicates an overall satisfaction rate of 9.58.This research provides power project safety managers with more advanced and comprehensive management tools,holding significant implications for the sustainable development of the power industry.
power projectsafety managementnatural language processingknowledge graph