摘要：This article adopts a research method that combined with theoretical analysis and system design,analyzes multiple dimensions of common safety hazard events, uses support vector machine classificationalgorithms to filter and mine valuable information in massive data, and establishes a common safety hazardevent feature set. This kind of technology can realize the automatic classification of safety hazards andextract their characteristic information, introduce the semantic analysis, word segmentation clusteringmethod to determine the typical processing measures of events, and generate knowledge items to addmethods and models to the processing measures database, which can solve the grid safety hazard data entryspecifications, In-depth analysis and other issues.
其他摘要：This article adopts a research method that combined with theoretical analysis and system design, analyzes multiple dimensions of common safety hazard events, uses support vector machine classification algorithms to filter and mine valuable information in massive data, and establishes a common safety hazard event feature set. This kind of technology can realize the automatic classification of safety hazards and extract their characteristic information, introduce the semantic analysis, word segmentation clustering method to determine the typical processing measures of events, and generate knowledge items to add methods and models to the processing measures database, which can solve the grid safety hazard data entry specifications, In-depth analysis and other issues.
