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From irregular to continuous: The deep Koopman model for time series forecasting of energy equipment
Date of Publication:2024-01-01
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