ABSTRACT. With the ongoing digitalization of industrial production, an increasing number of energy measuring points are installed in manufacturing ...
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 ...
The paper proposes the use of homomorphic encryption, which enables the possibility of training the deep learning and classical machine learning models whilst ...
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Oct 15, 2020 · This paper presents a machine learning process to forecast the very short term load of two machine tools, which can be utilized as a decision support basis.
Missing: Generic Approach for Production Machines
This paper presents a machine learning process to forecast the very short term load of two machine tools, which can be utilized as a decision support basis for ...
Generic Machine Learning Approach For Very Short Term Load Forecasting Of Production Machines. Proceedings of 11th International Conference on Applied Energy ...
Aug 29, 2024 · This paper provides a comprehensive survey on deep-learning-based STELF over the past ten years. It examines the entire forecasting 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 ...
A two-stage STLF model based on long short-term memory (LSTM) and multilayer perceptron (MLP), which improves the forecasting accuracy over the entire time ...
Abstract—This paper presents a generic strategy for short-term load forecasting (STLF) based on the support vector regression machines (SVR).