Anomaly detection method for building energy consumption in multivariate time series based on graph attention mechanism

ABSTRACT: A critical issue in intelligent building control is detecting energy consumption anomalies based on intelligent device status data. The building field is plagued by energy consumption anomalies caused by a number of factors, many of which are associated with one another in apparent temporal relationships. For the detection of abnormalities, most traditional detection methods rely solely on a single variable of energy consumption data and its time series changes. Therefore, they are unable to examine the correlation between the multiple characteristic factors that affect energy consumption anomalies and their relationship in time. The outcomes of anomaly detection are one-sided. To address the above problems, this paper proposes an anomaly detection method based on multivariate time series.

SUBMITTER: Zhang Z 

PROVIDER: S-EPMC10249861 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature