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  • 03b_Time_Series_AR_Testing
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Anomaly Detection. Time Series AR Testing

Anomaly detection Time series analysis Auto-regressive models IoT Internet of Things
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This workflow tests the performance of previously trained auto-regressive models for anomaly detection: - Filter the data to the maintenance window - Loop over each frequency column - Apply the previously trained model to the data - Calculate 1st level alarms based on the prediction errors - Calculate 2nd level alarms as the moving average of the 1st level alarms - Visualize the 2nd level alarms in a stacked area chart (all sensors) and a line plot (one sensor)

Used extensions & nodes

Created with KNIME Analytics Platform version 4.5.1
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    KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.1

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    KNIME JavaScript Views Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.1

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    KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

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    KNIME Math Expression (JEP) Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

  • Go to item
    KNIME Plotly Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

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    KNIME Timeseries nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.5.0

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