From irregular to continuous: The deep Koopman model for time series forecasting of energy equipment
Release Time:2024-09-01 Hits:
Date of Publication: 2024-05-16
Journal: Applied Energy
Volume: 364
ISSN: 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