The present application is applicable to the technical field of artificial intelligence. Provided are an anomaly detection method and apparatus, and a terminal and a storage medium. The method comprises: acquiring index data of a monitoring index at the current moment; acquiring, from among periodic components respectively corresponding to historical moments, a periodic component corresponding to the current moment; calculating a residual value of the index data according to the periodic component; and when the residual value is not within a residual threshold value range, determining that the monitoring index at the current moment is anomalous, wherein the process of acquiring the periodic components respectively corresponding to the historical moments comprises: by means of a convolutional noise reduction auto-encoder, carrying out noise reduction on first time sequence data of a monitoring index within a past preset time period, and outputting second time sequence data within the past preset time period; and decomposing the second time sequence data to obtain the periodic components respectively corresponding to the historical moments. Noise reduction is carried out on first time sequence data, such that the problem of noise interference during a periodic component decomposition process is ameliorated, and the detection precision of anomaly detection is improved.
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