Research on Intelligent Recognition Method of Risk Levels of Electricity Marketing Field Operation Types Based on Data Mining

Abstract

Electric power operation is an important component to ensure the continuous supply of electricity. However, electric power operation involves a wide range of complex processes, high-risk factors, personal injury, and other major accidents that occur from time to time. Although the rules and regulations of electric power safety production have been gradually improved, and the operation management mode has been optimized day by day, the low degree of digitization and intelligence still makes electric power operations face a high risk of major accidents. Against this background, this paper presents a study on the intelligent identification method of the risk level of power marketing field operation types based on data mining. Data mining technology is used to carry out research around the characteristics of electric power operations and their risk analysis, identification of accidental causes of electric power operations and analysis of accidental cause correlation, etc., and a scientific and reasonable accidental cause model of electric power operations is constructed. Subsequently, an intelligent identification method of power marketing field operation risk level and a violation assessment model are proposed. Then, the model performance test and empirical study are conducted with video data and a power marketing field operation event as experimental objects. The experimental results show that this paper’s method can accurately identify the power marketing field operation risk, and at the same time, in the actual power marketing field operation risk level identification test, the final risk prediction level derived from the use of this paper’s method is level 1.