On that account, a machine learning approach to forecast the electric load of production machines based on regression algorithms is presented in this paper ...
This paper presents a generic machine learning approach to forecast the very short term load of production machines which can be utilized as decision support ...
Generic Machine Learning Approach For Very Short Term Load Forecasting Of Production Machines ... Preprints and early-stage research may not have been peer ...
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It can be used as a blueprint to develop load forecasting models for other production machines using the historic load profile and various machine and process ...
The presented work focuses on deep learning for very short-term load forecasting of production machines as a basis for demand response applications on machine ...
The authors conclude that including production-planning data in the model could improve the result, especially for higher forecasting horizons. Petroşano et al.
It can be used as a blueprint to develop load forecasting models for other production machines using the historic load profile and various machine and process ...
Sep 30, 2024 · ... production and scheduling plans, thereby significantly enhancing the efficiency of the power system. ... Machine-Learning based methods in short- ...
Aug 29, 2024 · A comprehensive review on deep learning approaches for short-term load ... Review on probabilistic forecasting of photovoltaic power production ...
Jan 22, 2021 · STLF reduces the overall planning uncertainty added by the intermittent production of renewable sources; thus, it helps to minimize the ...