14-02-2024 дата публикации
Номер: KR20240018882A
Принадлежит:
Provided is a time series anomaly detection method using a GRU-based model. The method includes inputting time series data from a predetermined second to 1 second before a target point in time into a stacked GRU, outputting an output of the stacked GRU after passing through a fully connected layer, adding data from the predetermined second before the target point in time to an output value that has passed through the fully connected layer via a skip connection, and learning the GRU-based model to obtain predicted data at the target time point through actual data at the target time point and mean square error (MSE) loss on the basis of the added data. A similarity calculation unit is additionally provided to the GRU-based model, and the similarity calculation unit receives the time series data, generates latent variables, calculates a sum of similarities, and reflects importance of the latent variables, thereby learning the GRU-based model. This calculates a sum of similarities between variables ...
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