Matches in SemOpenAlex for { <https://semopenalex.org/work/W3090726677> ?p ?o ?g. }
Showing items 1 to 94 of
94
with 100 items per page.
- W3090726677 abstract "Unsupervised anomaly detection for time series is of great importance for various applications, such as Web monitoring, medical monitoring, and device fault diagnosis. Time series anomaly detection (TSAD) aims to find the observations that most different from others in a sequence of observations. With the development of deep learning, deep-autoencoder-based methods achieve state-of-the-art performance. These methods are usually able to find single anomaly points but fail to detect the anomaly segment and the change point. To tackle this problem, this paper proposes a novel TSAD method, which consists of a bidirectional LSTM (BiLSTM) autoencoder and a subsequent Gaussian segmentation model. BiLSTM encodes a time series in a predictive format from both positive and negative time directions, then outputs the latent feature vectors and restructured errors. After that, the latent features are used to find anomaly segments by the Gaussian segment model; the restructured errors are used to find change points and extreme single anomaly by a scoring function. In this way, our method can find all three kinds of anomaly points. Experiments on two real-world datasets demonstrate the effectiveness of the proposed method." @default.
- W3090726677 created "2020-10-08" @default.
- W3090726677 creator A5029412635 @default.
- W3090726677 creator A5031656256 @default.
- W3090726677 creator A5057879702 @default.
- W3090726677 creator A5069542053 @default.
- W3090726677 date "2020-07-01" @default.
- W3090726677 modified "2023-09-27" @default.
- W3090726677 title "One-step Predictive Encoder - Gaussian Segment Model for Time Series Anomaly Detection" @default.
- W3090726677 cites W1876967670 @default.
- W3090726677 cites W2062417985 @default.
- W3090726677 cites W2064675550 @default.
- W3090726677 cites W2118978333 @default.
- W3090726677 cites W2131774270 @default.
- W3090726677 cites W2132870739 @default.
- W3090726677 cites W2766761849 @default.
- W3090726677 cites W2905872298 @default.
- W3090726677 cites W2907759361 @default.
- W3090726677 cites W2948517885 @default.
- W3090726677 cites W2963460797 @default.
- W3090726677 cites W2965981069 @default.
- W3090726677 cites W2978669638 @default.
- W3090726677 cites W3098957257 @default.
- W3090726677 cites W3105825887 @default.
- W3090726677 cites W4243563432 @default.
- W3090726677 cites W4254182148 @default.
- W3090726677 doi "https://doi.org/10.1109/ijcnn48605.2020.9207569" @default.
- W3090726677 hasPublicationYear "2020" @default.
- W3090726677 type Work @default.
- W3090726677 sameAs 3090726677 @default.
- W3090726677 citedByCount "1" @default.
- W3090726677 countsByYear W30907266772022 @default.
- W3090726677 crossrefType "proceedings-article" @default.
- W3090726677 hasAuthorship W3090726677A5029412635 @default.
- W3090726677 hasAuthorship W3090726677A5031656256 @default.
- W3090726677 hasAuthorship W3090726677A5057879702 @default.
- W3090726677 hasAuthorship W3090726677A5069542053 @default.
- W3090726677 hasConcept C101738243 @default.
- W3090726677 hasConcept C108583219 @default.
- W3090726677 hasConcept C119857082 @default.
- W3090726677 hasConcept C121332964 @default.
- W3090726677 hasConcept C124101348 @default.
- W3090726677 hasConcept C127313418 @default.
- W3090726677 hasConcept C12997251 @default.
- W3090726677 hasConcept C138885662 @default.
- W3090726677 hasConcept C143724316 @default.
- W3090726677 hasConcept C151406439 @default.
- W3090726677 hasConcept C151730666 @default.
- W3090726677 hasConcept C153180895 @default.
- W3090726677 hasConcept C154945302 @default.
- W3090726677 hasConcept C163716315 @default.
- W3090726677 hasConcept C26873012 @default.
- W3090726677 hasConcept C2776401178 @default.
- W3090726677 hasConcept C41008148 @default.
- W3090726677 hasConcept C41895202 @default.
- W3090726677 hasConcept C62520636 @default.
- W3090726677 hasConcept C739882 @default.
- W3090726677 hasConceptScore W3090726677C101738243 @default.
- W3090726677 hasConceptScore W3090726677C108583219 @default.
- W3090726677 hasConceptScore W3090726677C119857082 @default.
- W3090726677 hasConceptScore W3090726677C121332964 @default.
- W3090726677 hasConceptScore W3090726677C124101348 @default.
- W3090726677 hasConceptScore W3090726677C127313418 @default.
- W3090726677 hasConceptScore W3090726677C12997251 @default.
- W3090726677 hasConceptScore W3090726677C138885662 @default.
- W3090726677 hasConceptScore W3090726677C143724316 @default.
- W3090726677 hasConceptScore W3090726677C151406439 @default.
- W3090726677 hasConceptScore W3090726677C151730666 @default.
- W3090726677 hasConceptScore W3090726677C153180895 @default.
- W3090726677 hasConceptScore W3090726677C154945302 @default.
- W3090726677 hasConceptScore W3090726677C163716315 @default.
- W3090726677 hasConceptScore W3090726677C26873012 @default.
- W3090726677 hasConceptScore W3090726677C2776401178 @default.
- W3090726677 hasConceptScore W3090726677C41008148 @default.
- W3090726677 hasConceptScore W3090726677C41895202 @default.
- W3090726677 hasConceptScore W3090726677C62520636 @default.
- W3090726677 hasConceptScore W3090726677C739882 @default.
- W3090726677 hasLocation W30907266771 @default.
- W3090726677 hasOpenAccess W3090726677 @default.
- W3090726677 hasPrimaryLocation W30907266771 @default.
- W3090726677 hasRelatedWork W114760076 @default.
- W3090726677 hasRelatedWork W1989643030 @default.
- W3090726677 hasRelatedWork W2161702708 @default.
- W3090726677 hasRelatedWork W2374590780 @default.
- W3090726677 hasRelatedWork W2376955565 @default.
- W3090726677 hasRelatedWork W2504418378 @default.
- W3090726677 hasRelatedWork W2534591110 @default.
- W3090726677 hasRelatedWork W2573169959 @default.
- W3090726677 hasRelatedWork W3192727092 @default.
- W3090726677 hasRelatedWork W4220696170 @default.
- W3090726677 isParatext "false" @default.
- W3090726677 isRetracted "false" @default.
- W3090726677 magId "3090726677" @default.
- W3090726677 workType "article" @default.