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While the number of private electrical facilities is increasing, there are not enough security personnel to perform the security work. In this paper, we propose a random forest model for predicting leakage current alarms in order to improve the efficiency of electrical safety operations. A random forest was created using periodic inspection data, alarm data, and meteorological data as explanatory variables, and generalization performance was evaluated by OOB-based F-measure. In order to obtain the highest performance, a grid search was performed to optimize the hyperparameters. As a result, it was possible to achieve alarm prediction with a certain level of performance. In addition, the optimal hyperparameters were found by grid search, and the F-measure was improved.

Optimal hyperparameters for random forest to predict leakage current alarm on premises