Research on Abnormal Identification Method of Power Grid Industrial Control System Based on Fuzzy Rules
Due to the large amount of uncertainty and ambiguity information in the power grid industrial control system,general identification methods are difficult to accurately identify its abnormal problems.Based on this,a fuzzy rule-based method for identifying anomalies in power grid industrial control systems is studied.Establish fuzzy rules between key features and abnormal category labels through a fuzzy rule table,calculate the matching degree between fuzzy features and fuzzy rule conditions,use Net Flow technology to collect flow data from power grid industrial control systems,and use a recursive information related feature selection algorithm to select key features,thereby inferring the category of abnormal problems.The experimental results show that the research method can accurately identify abnormal problems in the power grid industrial control system,and the Matthews correlation coefficient obtained is larger and closer to 1.
fuzzy rulespower gridindustrial control systemnet flow technologykey featuresanomaly recognition methods
万方数据
维普
