RECONSTRUCTING TIME SERIES DATASETS WITH MISSING VALUES UTILIZING MACHINE LEARNING

摘要

An apparatus comprises a processing device configured to obtain a time series dataset having missing values, the time series dataset comprising monitoring data associated with one or more assets. The processing device is also configured to generate, utilizing a machine learning algorithm, a reconstructed time series dataset having imputed values for the missing values in the obtained time series dataset, the machine learning algorithm comprising a generative network implementing inverse network parameter determination for network parameters of the generative network. The processing device is further configured to classify patterns in the obtained time series dataset utilizing the reconstructed time series dataset, to select remedial actions for controlling at least one of the one or more assets based at least in part on the classified patterns in the obtained time series dataset, and to initiate the selected remedial actions to control the at least one asset.