Matches in SemOpenAlex for { <https://semopenalex.org/work/W2898828531> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W2898828531 abstract "In the modern world, time series data has become a critical part of many systems underlying various types that are recorded to reflect the status of objects according to the timeline. There are many kinds of research investigating to automate the process of analyzing time series data. Long Short-Term Memory (LSTM) network have been demonstrated to be a useful tool for learning sequence data. In this paper, we explore LSTM based approach to analyzing temporal data for abnormal detection. Stacked Long Short-Term Memory (LSTM) network is utilized as a predictor which is trained on normal data to learn the higher level temporal features, then such predictor is used to predict future values. An error-distribution estimation model is built to calculate the anomaly in the score of the observation. Anomalies are detected using a window-based method based on anomaly scores. To prove the promise applicable potential of our approach, we conducted the experiment on some domains (industry system, health monitor system, social based event detection system) come up with time series data including power consumption, ECG signal, and social data respectively." @default.
- W2898828531 created "2018-11-09" @default.
- W2898828531 creator A5035630816 @default.
- W2898828531 creator A5043486744 @default.
- W2898828531 creator A5060943530 @default.
- W2898828531 creator A5083270410 @default.
- W2898828531 creator A5083642709 @default.
- W2898828531 date "2018-08-01" @default.
- W2898828531 modified "2023-10-02" @default.
- W2898828531 title "Applications of Anomaly Detection Using Deep Learning on Time Series Data" @default.
- W2898828531 cites W1650484478 @default.
- W2898828531 cites W2064675550 @default.
- W2898828531 cites W2122646361 @default.
- W2898828531 cites W2278984902 @default.
- W2898828531 cites W2621033546 @default.
- W2898828531 cites W3098072737 @default.
- W2898828531 doi "https://doi.org/10.1109/dasc/picom/datacom/cyberscitec.2018.00078" @default.
- W2898828531 hasPublicationYear "2018" @default.
- W2898828531 type Work @default.
- W2898828531 sameAs 2898828531 @default.
- W2898828531 citedByCount "8" @default.
- W2898828531 countsByYear W28988285312019 @default.
- W2898828531 countsByYear W28988285312020 @default.
- W2898828531 countsByYear W28988285312021 @default.
- W2898828531 countsByYear W28988285312023 @default.
- W2898828531 crossrefType "proceedings-article" @default.
- W2898828531 hasAuthorship W2898828531A5035630816 @default.
- W2898828531 hasAuthorship W2898828531A5043486744 @default.
- W2898828531 hasAuthorship W2898828531A5060943530 @default.
- W2898828531 hasAuthorship W2898828531A5083270410 @default.
- W2898828531 hasAuthorship W2898828531A5083642709 @default.
- W2898828531 hasConcept C105795698 @default.
- W2898828531 hasConcept C108583219 @default.
- W2898828531 hasConcept C111919701 @default.
- W2898828531 hasConcept C119857082 @default.
- W2898828531 hasConcept C121332964 @default.
- W2898828531 hasConcept C124101348 @default.
- W2898828531 hasConcept C12997251 @default.
- W2898828531 hasConcept C133488467 @default.
- W2898828531 hasConcept C143724316 @default.
- W2898828531 hasConcept C147168706 @default.
- W2898828531 hasConcept C151406439 @default.
- W2898828531 hasConcept C151730666 @default.
- W2898828531 hasConcept C154945302 @default.
- W2898828531 hasConcept C26873012 @default.
- W2898828531 hasConcept C2779662365 @default.
- W2898828531 hasConcept C33923547 @default.
- W2898828531 hasConcept C41008148 @default.
- W2898828531 hasConcept C4438859 @default.
- W2898828531 hasConcept C50644808 @default.
- W2898828531 hasConcept C62520636 @default.
- W2898828531 hasConcept C67186912 @default.
- W2898828531 hasConcept C739882 @default.
- W2898828531 hasConcept C77088390 @default.
- W2898828531 hasConcept C77277458 @default.
- W2898828531 hasConcept C86803240 @default.
- W2898828531 hasConcept C98045186 @default.
- W2898828531 hasConceptScore W2898828531C105795698 @default.
- W2898828531 hasConceptScore W2898828531C108583219 @default.
- W2898828531 hasConceptScore W2898828531C111919701 @default.
- W2898828531 hasConceptScore W2898828531C119857082 @default.
- W2898828531 hasConceptScore W2898828531C121332964 @default.
- W2898828531 hasConceptScore W2898828531C124101348 @default.
- W2898828531 hasConceptScore W2898828531C12997251 @default.
- W2898828531 hasConceptScore W2898828531C133488467 @default.
- W2898828531 hasConceptScore W2898828531C143724316 @default.
- W2898828531 hasConceptScore W2898828531C147168706 @default.
- W2898828531 hasConceptScore W2898828531C151406439 @default.
- W2898828531 hasConceptScore W2898828531C151730666 @default.
- W2898828531 hasConceptScore W2898828531C154945302 @default.
- W2898828531 hasConceptScore W2898828531C26873012 @default.
- W2898828531 hasConceptScore W2898828531C2779662365 @default.
- W2898828531 hasConceptScore W2898828531C33923547 @default.
- W2898828531 hasConceptScore W2898828531C41008148 @default.
- W2898828531 hasConceptScore W2898828531C4438859 @default.
- W2898828531 hasConceptScore W2898828531C50644808 @default.
- W2898828531 hasConceptScore W2898828531C62520636 @default.
- W2898828531 hasConceptScore W2898828531C67186912 @default.
- W2898828531 hasConceptScore W2898828531C739882 @default.
- W2898828531 hasConceptScore W2898828531C77088390 @default.
- W2898828531 hasConceptScore W2898828531C77277458 @default.
- W2898828531 hasConceptScore W2898828531C86803240 @default.
- W2898828531 hasConceptScore W2898828531C98045186 @default.
- W2898828531 hasLocation W28988285311 @default.
- W2898828531 hasOpenAccess W2898828531 @default.
- W2898828531 hasPrimaryLocation W28988285311 @default.
- W2898828531 hasRelatedWork W2063729131 @default.
- W2898828531 hasRelatedWork W2898828531 @default.
- W2898828531 hasRelatedWork W2951038762 @default.
- W2898828531 hasRelatedWork W2990226253 @default.
- W2898828531 hasRelatedWork W3022024545 @default.
- W2898828531 hasRelatedWork W3172675883 @default.
- W2898828531 hasRelatedWork W3192727092 @default.
- W2898828531 hasRelatedWork W4205438547 @default.
- W2898828531 hasRelatedWork W4288020863 @default.
- W2898828531 hasRelatedWork W4386249425 @default.
- W2898828531 isParatext "false" @default.
- W2898828531 isRetracted "false" @default.
- W2898828531 magId "2898828531" @default.
- W2898828531 workType "article" @default.