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References from Typical load profile-supported convolutional neural network for short-term load forecasting in the industrial sector. Local targets link to admitted publications; unresolved targets remain external evidence.
A survey of machine learning models in renewable energy predictions
10.3390/app10175975 · 2020 · External reference
Unresolved reference
2019 · External reference
Unresolved reference
2016 · External reference
Energieflexibel durch bivalente Produktionsanlagen: mit bivalent ausgelegten Produktionsprozessen Energiekosten senken und das Stromnetz stabilisieren
10.37544/1436-4980-2017-05-62 · 2017 · External reference
10.3390/en13225887
10.3390/en13225887 · External reference
A sensor reduced machine learning approach for condition-based energy monitoring for machine Tools
2019 · External reference
Machine learning based very short term load forecasting of machine tools
10.1016/j.apenergy.2020.115440 · 2020 · External reference
10.1016/j.egyai.2020.100009 · 2020 · Admitted local publication
Readiness of short-term load forecasting methods for their deployment on company level
2021 · External reference
Unresolved reference
2020 · External reference
Short-term industrial load forecasting: a case study in an italian factory
2021 · External reference
A methodology for customized prediction of energy consumption in manufacturing industries
10.1007/s40684-015-0021-z · 2015 · External reference
Day-ahead industrial load forecasting for electric RTG cranes
10.1007/s40565-018-0394-4 · 2018 · External reference
10.1016/j.procir.2019.01.060
10.1016/j.procir.2019.01.060 · External reference
Designing, developing and validating a forecasting method for the month ahead hourly electricity consumption in the case of medium industrial consumers
10.3390/pr7050310 · 2019 · External reference
A generic energy prediction model of machine tools using deep learning algorithms
10.1016/j.apenergy.2020.115402 · 2020 · External reference
Integrating digitization technologies into resource efficiency driven industrial learning environments
2018 · External reference
Unresolved reference
2009 · External reference
Unresolved reference
External reference
Classification and clustering of electricity demand patterns in industrial parks
10.3390/en5125215 · 2012 · External reference
Unresolved reference
2010 · External reference
Very short-term load forecasting using artificial neural networks
10.1109/59.852131 · 2000 · External reference
Unresolved reference
External reference
Unresolved reference
2015 · External reference
Applying energy building simulation in the assessment of energy efficiency measures in factories
2018 · External reference
Unresolved reference
External reference
Unresolved reference
External reference
Deep learning based on multi-decomposition for short-term load forecasting
10.3390/en11123433 · 2018 · External reference
Unresolved reference
2018 · External reference
Very short-term electricity load demand forecasting using support vector regression
2009 · External reference
A novel data-driven approach for residential electricity consumption prediction based on ensemble learning
10.1016/j.energy.2018.02.028 · 2018 · External reference
Unresolved reference
2018 · External reference
Unresolved reference
1997 · External reference
Robust ensemble learning framework for day-ahead forecasting of household based energy consumption
10.1016/j.apenergy.2017.12.054 · 2018 · External reference
A data mining method for short-term load forecasting in power systems
10.1002/eej.1150 · 2002 · External reference
Daily load profiles clustering: a powerful tool for demand side management in medium-sized industries
2017 · External reference
Classification and regression trees
10.2307/2530946 · 1984 · External reference
Unresolved reference
1997 · External reference
Unresolved reference
External reference
Short-term load forecasting based on an adaptive hybrid method
10.1109/tpwrs.2005.860944 · 2006 · External reference
