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From irregular to continuous: The deep Koopman model for time series forecasting of energy equipment

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Date of Publication:2024-05-16

Journal:Applied Energy

Volume:364

ISSN No.:0306-2619

Key Words:Data driven; Data handling; Deep neural networks; Digital modeling; Energy equipments; equipment; Fluidized beds; Forecasting; Irregular time series; Koopman operator; management practice; Model management; Multi-step-ahead predictions; sensor; Sequence models; time series; Time series; Time-series data; Time series forecasting; wind turbine

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