SYSTEMS AND METHODS FOR PREDICTING INFORMATION HANDLING RESOURCE FAILURES USING DEEP RECURRENT NEURAL NETWORK WITH A MODIFIED GATED RECURRENT UNIT HAVING MISSING DATA IMPUTATION

SYSTEMS AND METHODS FOR PREDICTING INFORMATION HANDLING RESOURCE FAILURES USING DEEP RECURRENT NEURAL NETWORK WITH A MODIFIED GATED RECURRENT UNIT HAVING MISSING DATA IMPUTATION

A method may include receiving telemetry data associated with one or more information handling resources, receiving failure statistics associated with the one or more information handling resources, merging the telemetry data and the failure statistics to create training data, and implementing a gat...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: SINGH, Ashutosh, CHAMBERS, Landon Martin
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
ELECTRIC DIGITAL DATA PROCESSING
PHYSICS
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Beschreibung
Zusammenfassung:A method may include receiving telemetry data associated with one or more information handling resources, receiving failure statistics associated with the one or more information handling resources, merging the telemetry data and the failure statistics to create training data, and implementing a gated recurrent unit to: (i) impute missing values from the training data and (ii) train a pattern recognition engine configured to predict a failure status of an information handling resource from operational data associated with the information handling resource.