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Research on Anomaly Pattern Detection in Hydrological Time Series

https://doi.org/10.1109/wisa.2017.73
0 signed · 15 inferred · view as graph

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1145/335191.335388openalex-snapshot
LOF
inferredcites →https://doi.org/10.1155/2014/879736openalex-snapshot
Time Series Outlier Detection Based on Sliding Window Prediction
inferredcites →https://doi.org/10.1504/ijbidm.2015.072212openalex-snapshot
An efficient method for motif and anomaly detection in time series based on clustering
inferredcites →https://doi.org/10.2307/1270165openalex-snapshot
Estimation of Time Series Parameters in the Presence of Outliers
inferredcites →https://doi.org/10.5860/choice.49-3305openalex-snapshot
Data mining: concepts and techniques

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4662943openalex-extracted
An Automated Machine Learning Approach for Detecting Anomalous Peak Patterns in Time Series Data from a Research Watershed in the North Eastern United States Critical Zone
inferred← citeshttps://doi.org/10.1007/978-3-030-55180-3_2openalex-snapshot
Detection of Anomalous Patterns in Water Consumption: An Overview of Approaches
inferred← citeshttps://doi.org/10.1007/978-3-031-35445-8_11openalex-snapshot
Peak Anomaly Detection from Environmental Sensor-Generated Watershed Time Series Data
inferred← citeshttps://doi.org/10.1007/978-981-15-0184-5_66openalex-snapshot
Timestamp Anomaly Detection Using IBM Watson IoT Platform
inferred← citeshttps://doi.org/10.1007/s40747-021-00442-6openalex-snapshot
An edge-cloud collaboration architecture for pattern anomaly detection of time series in wireless sensor networks
inferred← citeshttps://doi.org/10.3389/frwa.2020.562304openalex-snapshot
Toward Urban Water Security: Broadening the Use of Machine Learning Methods for Mitigating Urban Water Hazards
inferred← citeshttps://doi.org/10.3390/w13131862openalex-snapshot
Anomaly Detection Using a Sliding Window Technique and Data Imputation with Machine Learning for Hydrological Time Series
inferred← citeshttps://doi.org/10.3390/w15081635openalex-snapshot
Application of Deep Learning in Drainage Systems Monitoring Data Repair—A Case Study Using Con-GRU Model
inferred← citeshttps://doi.org/10.70675/fe9f80cdz04cez4836zaa46z252893548206openalex-snapshot
Contributions to the detection and ordering of variable length discords with application to climatedata series
inferred← citeshttps://doi.org/10.7717/peerj-cs.1664openalex-snapshot
FedLGAN: a method for anomaly detection and repair of hydrological telemetry data based on federated learning
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